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Learning astronomy through Augmented Reality: EduINAF resources to enhance students’ motivation and understanding
<p>In this presentation, we will illustrate Augmented Reality (AR) resources developed by INAF (The Italian National Institute of Astrophysics) for communicating astronomy, distributed to schools and the general public by EduINAF, the online magazine devoted to education and outreach, (https://edu.inaf.it/). The impact of these initiatives and future perspectives will also be provided. AR and other innovative technologies have a very high potential in astronomy communication, outreach and education. By adding texts, images, overlays, sounds and other effects, AR enhances users’ experience, allowing personal and interactive choices and offering unique educational opportunities. Due to its benefits of providing an engaging and immersive learning space, the use of AR in education has been recognized as a powerful instrument for educators and students.  Among the first attempts and experiments with AR, in 2019 we created an augmented reality app - both in Italian and English - dedicated to the Museum of Specola inside the Astronomical Observatory of Palermo, in order to promote the cultural heritage of the institute. Using a simple tool like the app <em>Zappworks Studio Widgets</em> and a smartphone, the public could interact with the history and the instruments held in the museum, choosing between seven different levels of information. In 2020 - on the occasion of “Esperienza InSegna 2020”, a science fair for schools, which every year counts about 15.000 participants - INAF created an interactive game called “Terra Game” using Metaverse Studio. Discovering the “ingredients for life” and the composition, temperature and atmosphere of different planets, students were able to understand how special the Earth is in comparison to the other planets of the Solar System and to exoplanets orbiting around other stars. In 2021, to catch teenage students’ attention, we integrated new technologies in the learning path dedicated by EduINAF to Mars on the occasion of the landing on Mars of NASA’s rover Perseverance. We developed the augmented reality experience “MARS2020 Perseverance” with <em>Zap works Studio Design</em>, showing the objectives of the mission, other rovers landed on Mars and the sophisticated instruments onboard. Using this app people can discover the instruments used by the rover for acquiring information about Martian geology, atmosphere, environmental conditions and potential biosignatures. The app also gives the opportunity to visit NASA resources and take a selfie with the Perseverance and the drone Ingenuity and share the pictures with friends through social media. To mark the event of the <em>Supermoon</em> of 26th May 2021 EduINAF also published educational resources dedicated to the moon. Among these, the augmented reality experience “Maree Lunatiche”, developed with Zap works Studio Design. This app explains the phenomenon of tides. From the menu, there is also the opportunity to interact with a 3D model of the moon and to take a selfie with the full moon. The impact of these and other AR initiatives in EduINAF, as well as their future perspectives, will also be provided in this talk.</p>
<p><img src="data:image/jpeg;base64, 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Calibration of the NOMAD-LNO channel onboard ExoMars 2016 Trace Gas Orbiter using solar spectra
<p><strong>Calibration of the NOMAD-LNO channel onboard ExoMars 2016 Trace Gas Orbiter using solar spectra</strong></p>
<p><strong>Cruz Mermy </strong>(1), F. Schmidt (1), I. R. Thomas (2), F. Daerden (2), B. Ristic (2), M. R. Patel (3,4), J.-J. Lopez-Moreno (5), G. Bellucci (6), A. C. Vandaele (2) and the NOMAD Team</p>
<p><strong>Introduction</strong></p>
<p>The LNO channel is a compact high-resolution echelle grating spectrometer with an acousto-optic tunable filter (AOTF) working in the infrared domain from 2.3 μ m to 3.8 μ m (4250-2630 cm -1 ) with a resolving power ( λ / Δ λ ) of around 10000, specially designed for nadir observation. With such high resolving power combined with the near-circular orbit of TGO that allow completion of 12 orbits in one sol, promoting a global coverage of the planet, the NOMAD-LNO instrument fits in with the science objective of the ExoMars program [Vandaele2015, Vandaele2018] and is perfectly suited to study the martian surface and atmosphere. The main objective here is to propose an original calibration procedure, adaptable for the full dataset of NOMAD-LNO. This calibration is complementary to the one proposed by [I.R.Thomas2021] in the sense that we will not assume the temporal stability of the instrument here. Our approach is thus able to test the temporal stability of the instrument in front of degradation by energetic particles. This approach will be based on an empirical continuum removal to take into account the departure between actual blaze function and theoretical one.</p>
<p><strong>Dataset</strong></p>
<p>The NOMAD-LNO fullscans is a solar observation made for calibration purposes. The instrument, normally in nadir position, is pointing toward the sun. The choice of using solar fullscans was made for two reasons: first, there are not enough miniscans to cover all diffraction orders with a significant amount of data while fullscans always cover the whole spectral range which allows testing the time dependence of the calibration. Second, it is important to estimate the instrumental sensitivity over the whole diffraction order range. As of June 2020, six solar calibrations have been performed. Typical fullscan observation is shown in figure 1 the x-axis is the spectel number, the y-axis is the diffraction order (i.e. the AOTF frequency) and the z-axis shows the sensitivity of the detector (in ADU for Analog to Digital Units).</p>
<p><img src="data:image/png;base64, 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|
Newly Recognized QSO/Galaxy Pairs at Small Impact Parameters for Low Redshift Galaxies
A search for emission lines in foreground galaxies, in QSO spectra (zgal 5 x 10-17 ergs cm-2 s-1 • Confirmed additional, expected galactic emissions at the same redshift as H to weed out false positives: H, H, [O III], [O II], [N II], [S II] • Emission line search produced 21 examples of QSOs overlapped by foreground low redshift galaxies (QSO/Galaxy pairs). Figure 2: Composite SDSS image of QJ1042+0748 (the blue object just above center). The QSO is at z=2.665. Emission lines (Figure 1) from the spectrum of the overlaying galaxy are at z=0.03321. Figure 1: The SDSS spectrum of QJ1042+0748, a z=2.665 QSO with a superimposed spectrum of a (narrow-line) galaxy from an object that falls in the SDSS fiber. PHOTOMETRY • IDL and IDP3 software used to de-blend the overlapped QSO/Galaxy pairs • Color magnitudes for each galaxy obtained by subtracting an adjusted PSF to remove the paired QSO • Color magnitudes for each QSO obtained by measuring the magnitudes of the fitted PSF MEASURED PROPERTIES QSO g and i-band magnitudes Galaxy u and r-band magnitudes QSO (g-i) [observer-frame color excess] QSO E(B-V)g-i [absorber-frame color excess; extinction measure] Star Formation Rate H/H Flux Ratio QSO/Galaxy centroid offset [impact parameter] Galactic length, width, and orientation QSOALS Expectations • Each QSO/Galaxy pair spectrum was searched for expected absorption features due to the foreground galaxy. • Ca II and Na I lines were identified and measured for equivalent widths and errors using IRAF. • Table 3 shows the relevant absorption features for best pairs. |
Stratigraphic studies of Ganymede’s tectonic activity in the bright terrain: results from the Byblus Sulcus and Harpagia Sulcus regions
<p>The Jovian satellite Ganymede experienced a pronounced period of tectonic resurfacing forming the extended bright or light terrain the so-called <em>Sulci</em>, which cover about 2/3 of Ganymede’s surface (Pappalardo et al., 2004 and references therein). It crosscuts the older dark terrain of the so-called regions by long swaths of subparallel grooves or separates the different regions by a complex network of tens to kilometer wide polygons/cells (Patterson et al., 2010, Collins et al., 2013), with each cell being characterized by a different density and orientation of the structural grooves. Previous studies indicated that different tectonic styles are apparent reaching from roughly evenly spaced grooves oriented in a single dominant direction to smooth surface areas with only faint or undetectable grooves at decameter to kilometer resolution (Collins et al., 1998, Patterson et al., 2010) with cryovolcanic resurfacing playing a possible role in the formation of the latter.</p>
<p> </p>
<p>In order to better understand the formation of the bright terrain and its possible interaction with a subsurface ocean its investigation has been made one of the top goals of the upcoming JUICE mission (Grasset et al., 2013). For the purpose of preparing for the JUICE mission and maximizing its science return, we re-investigate the available Voyager ISS and Galileo SSI data set. Our focus lies on the characterization of the bright terrain, its contact to the dark terrain, the definition and characterization of the tectonic subunits/cells and their stratigraphic relationship to each other. The work is supported by the estimation of the surface ages from crater frequency distributions and compositional information derived from Galileo NIMS data. The goal is to study the local formation process and to identify any changes in tectonic style through time, but also to compare the formation process of the bright terrain across Ganymede’s entire surface in order to reveal any global/regional differences in the past tectonic activity, and to characterize possible differences and similarities of the bright terrain at different locations on the body.</p>
<p> </p>
<p>Among the studied areas are a portion of <em>Byblus Sulcus</em> (~40°N/160°E) and of <em>Harpagia Sulcus</em> (~16°S/50°E) located in the northern portion of the anti-Jovian hemisphere and in the southern portion of the sub-Jovian hemisphere, respectively. <em>Byblus Sulcus</em> is a 30 km broad and NNW-SSE oriented band reaching from <em>Philus Sulcus</em> into the dark terrain of <em>Marius Regio</em>, where it meets the east-west trending grooved lane named <em>Akitu Sulcus</em>, which is truncated by the grooved and smooth terrain of<em> Byblus Sulcus </em>and thus is relatively older. Whereas the ancient neighboring dark terrain is already highly furrowed, <em>Byblus Sulcus</em> is mainly characterized by grooved terrain (<em>lgf </em>and<em> lgc</em>) and smaller areas of smooth terrain (<em>ls</em>) on its northern border to the dark terrain of<em> Marius Regio. Byblus Sulcus</em> is superimposed by small two dark floor craters with a dark inner and bright outer halo of ejecta material representing the youngest features in this region.</p>
<p> </p>
<p>The imaged portion of <em>Harpagia Sulcus</em> covers a 20-km broad region of bright or light material units including the light grooved terrain (<em>lg</em>), a smooth-subdued terrain in the middle (<em>ls</em>), the lineated terrains (<em>ll</em>) on either sides of the smooth-subdued terrain and a region of undivided terrain (<em>undiv</em>) on the southern side of the Sulcus. The smooth-subdued terrain accounts for a comparably large number of craters as compared to other terrains and is being crosscut by the lineated terrains on either sides and the light grooved terrain on the eastern and southern sides, evidenced by the presence of sharp boundaries separating them. So, the smooth-subdued terrain is supposed to be older than other terrains. The light grooved terrain is supposed to be much younger terrain since it crosscuts the lineated terrain and accounts for the smaller number of craters. Lineated terrains to be intermediate in age between light grooved terrain and smooth-subdued terrain. Nevertheless, crater density frequency indicates a narrow timescale.</p>
<p>While the crater frequency areas of measurement of the dark terrain units in <em>Byblus Sulcus</em> are clearly higher than those from bright terrain, inferring a higher age, the bright units in both the <em>Byblus</em> and <em>Harpagia Sulcus</em> show crater frequencies more or less identical within measurement uncertainties. Whether this is a general feature of Ganymede’s bright terrain, or specific to these two selected regions, will be a major issue in our ongoing studies. Also, bright grooved and smooth units cannot be separated very well in terms of crater frequencies in both regions. Since the existing cratering chronology models by Neukum et al. (1998) and Zahnle et al. (2003) are highly uncertain, it is difficult to infer if Ganymede was tectonically active only over a short period of time or over a much longer period, as implied by low impact rates in the Jovian system (e.g., Zahnle et al., 2003).</p>
<p><strong><img src="data:image/png;base64, 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 |
SSHADE-BandList, the new database of spectroscopy band lists of solids
<p><strong>Introduction </strong></p>
<p>The SSHADE database infrastructure (1) (http://www.sshade.eu) hosts the databases of about 30 experimental research groups in spectroscopy of solids from 15 countries. It currently provides to all researcher over 4000 spectra of many different types of solids (ices, minerals, carbonaceous matters, meteorites…) over a very wide range of wavelengths (mostly X-ray and VUV to sub-mm)</p>
<p>However, although these data are invaluable for the community, one type of information is still critically missing to easily interpret observations: the list of the characteristics of all the absorption bands of a given solid, called its ‘band list’.</p>
<p>This type of database is well developed for gases (see e.g. the VAMDC portal (2)), and it is even frequently the only type of spectral data available. But for solids (and liquids) there is currently almost no database which provide such information (only in some restricted fields, such as Raman spectroscopy of minerals, e.g. the WURM database (3)).<strong>  </strong></p>
<p>This critical lack triggered us to develop such a band list database containing the characteristics of electronic, vibration and phonon bands of various solids (ices, simple organics, minerals) of astrophysical interest to help:</p>
<ul>
<li>identify absorption or emission bands from solids observed in various astrophysical environments or in laboratory simulations</li>
<li>determine the environment of the molecule or mineral (composition, isotopes, mixing, phase, T, P, …)</li>
<li>select the best spectra in SSHADE to compare with observation, or to use in models</li>
</ul>
<p><strong>What is a band list of a solid?</strong></p>
<p>A ‘band list’ is a list of band parameters and vibration modes of a molecule in a simple molecular constituent (3 species maximum), or of a mineral or a ionic/covalent solid,  with a well-defined phase and composition (fixed or small range). It includes the bands of all isotopes (sub-bandlists) and can be provided for different environments (T, P, …).</p>
<p>The SSHADE 'band list' database provides the band parameters (position, width, peak and/or integrated intensity, and their accuracy, isotopic species involved, mode assignment, ...) of a progressively increasing number of solids and simple compounds (with different compositions) of astrophysical and planetary interest in various phases (crystallines, amorphous, ...) at different temperatures or pressures.</p>
<p>We are feeding this database through exhaustive compilations and critical reviews of all data published in various journals for pure ices and molecular solids and their simple compounds (solid solution, hydrates, clathrates, ...), including the own works of the SSHADE consortium partners. We will continue in a second step with band lists of minerals. However, this is a tremendous scientific work, expected to last many years… For example, the infrared spectrum of pure solid CO in its cubic α phase has been the subject of more than 35 papers scattered in 25 different journals over the period 1961-2020…</p>
<p><strong>SSHADE band list database and interface</strong></p>
<p>A specific data model, SSDM-BL (Solid Spectroscopy Data Model – Band List), has been first developed in order to accurately describe and link all the parameters necessary to describe both the solid constituent and the band list itself. A structured database storing all these data and metadata, has then be set up based on this data model. A data review tool (excel file), a data convertor to a XML import file, as well as a data import tool have been developed to feed the database.</p>
<p>Then an efficient search tool allows you to search either a band list or a specific band thanks to a combination between a ‘search bar’ and a set of filters on various parameters, such as band position, width and intensity, expected molecular or atomic composition, type of vibration, temperature and pressure. The search result are provided as a table with band list title or the main band parameters allowing the users to select the most relevant ones. He can then display the selected band list graphically, thanks to a simulator of ‘band list spectra’, with various unit and display options. The data can be exported as a table containing the main parameters of all the bands of the band list, as well as detailed metadata of the band list and all its bands. A data reference and a DOI will be associated with each band list.</p>
<p><img src="data:image/png;base64, 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SdiHx/ZsH373jdjQQOD4keG3/8+zf1dseGBkw7uOTR9Eersz4RCCEADgcrk2bNiQTqd37tw5MjISCoU2btzY2NgIAOjq6nr99de7u7sdDseePXt6enr27NmjVqtPnjy5ZcuWbGva1q1bN2/eHAwG/X4/Xm3Pnj2dnZ0ffvhhJBLBydl4cGtr6549e5LJpEKhOHLkyL59+7RabSAQ2Lx5c39/v1wuHxkZ2b59u/AEjx49unfvXoSQVCrdvXv30aNHNRpNKBTavHkzFpdDQ0O7du0CACCEhoeHd+zYIWitUCi0ffv25uZmhJDX643FYkePHm1qatq+fXsikejp6dm/f38mkyEI4uOPP7bZbARBtLS0HD58GACwadMmu9 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Social change innovations, citizen science, miniSASS and the SDGs
The United Nations Sustainable Development Goals (SDGs) describe a course of action to address poverty, protect the planet and ensure prosperity for all (https://sdgs.un.org/goals). More speci fi cally, SDG 6 clari fi es how water quality, quantity and access are crucial to human well-being, and yet human activities are compromising water resources through over-exploitation, pollution, as well as contributing to the spread of disease. Globally aquatic ecosystems are highly threatened and concerted efforts by governments and civil society to ‘ turn the situation around ’ are simply not working. Human-created problems require human-centred solutions and these require different ways of thinking and acting to those behaviour patterns that are contributing to the challenges. In this paper, we fi rst consider causal approaches to attitude change and behaviour modi fi cation that are simply not working as intended. We then explore enabling responses such as citizen science and co-engaged action learning as more tenable alternatives. SDG 6 has a focus on clean water and sanitation for all. The SDGs further clarify how the extent to which this goal can be realized depends, to a large extent, on stakeholder engagements and education. Through stakeholder engagements and educational processes, people can contribute towards SDG 6 and the speci fi c indicator and target in SDG 6.b – Stakeholder participation. Following a three-year research process, that investigated a wide range of participatory tools, this paper explores how the Stream Assessment Scoring System (miniSASS; www.minisass.org) can enable members of the public to engage in water quality monitoring at a local level. The paper continues to demonstrate how miniSASS can contribute to the monitoring of progress towards Sustainable Development Goal Target 6.3, by providing a mechanism for data collection indicator 6.3.2. miniSASS is proving popular in southern Africa as a methodology for engaging stakeholder participation in water quality monitoring and management. The technique costs very little to implement and can be applied by children and scientists alike. As a biomonitoring approach, it is based on families of macroinvertebrates that are present in most perennial rivers of the world. The paper concludes by describing how useful the miniSASS technique can be for addressing data gaps for SDG 6.3.2 reporting, and that it can be applied in most regions of the world. (cid:129) This paper demonstrates how citizen-derived data through the stream assessment scoring system (miniSASS) can be used for SDG 6 reporting on water quality. (cid:129) It explores the expansion of miniSASS to collect water quality data globally. (cid:129) miniSASS supports policy by mobilizing society to engage with water issues.
INTRODUCTION
Conventional wisdom continues to fail us Conventional wisdom approaches, which often emphasize attitude change with the assumption that behavioural practices will follow have not proved tenable (Beck, 1992(Beck, , 1995(Beck, , 1997Kemmis & Mutton, 2012). Fien (2003) emphasizes that 'among the most successful [environmental education] programmes are those that avoid the belief that awareness leads to understanding, understanding leads to concern, and concern motivates the development of skills and action (our italics)' (Fien, 2003). Causal, linear, top-down or centre-to-periphery approaches that assume behaviour change, following awareness raising, often facilitate a power-gradient from those who feel they know to those who they feel ought to know. This rational logic continues to assume that once informed, the others, often described as a target group 1 , will change accordingly! As reported above, this rational change process fails to meet expectations and, at times, may even alienate the very people it is seeking to change (Taylor, 2010).
The sustainable development goals and SDG 6 SDG 6 has a focus on clean water and sanitation for all. The SDGs further clarify how the extent to which this goal can be realized depends, to a large extent, on stakeholder engagements and education. Through stakeholder engagements and educational processes, people can contribute towards SDG 6 and the specific indicator and target in SDG 6.b -Stakeholder participation, namely: 'Support and strengthen the participation of local communities in improving water and sanitation management' The United Nations (UN) are explicit as to why stakeholder participation is important, but a key research question is how this participation can be meaningful and engaging, particularly the aspect of improving water management: 'Target 6.b aims for the participation of local communities in water and sanitation planning and management, which is essential for ensuring that the needs of all people are being met. The involvement of relevant stakeholders is further necessary to ensure: that the technical and administrative solutions decided upon are suitable for specific socioeconomic contexts, the full understanding of the impacts of a certain development decision and the encouragement of local ownership of the solutions when implemented (to ensure sustainability over time). Target 6.b supports the implementation of all SDG 6 targets (targets 6.1-6.6 and 6.a) by promoting the meaningful involvement of local communities, which is also a central component of IWRM' 2 .
1 The use of the term target group, a metaphor from military operations, emphasizes the causal tradition of 'getting the message across.' It is therefore difficult to apply in a more inclusive, dialogue-centred manner. By classifying people as 'the other' it militates against an opportunity for relationship building, mutual learning, deliberation and a commitment to building understanding and human dignity. 2 https://www.sdg6monitoring.org/indicators/target-6b/ A detailed three-year research process, supported by the Water Research Commission, investigated a wide range of public participation approaches to water quality issues and clarified how citizen science can play a meaningful role in water-related issues (Graham & Taylor, 2018). Of all the citizen science tools that were reviewed, miniSASS stood out as a relatively easy technique to use, that can be applied at virtually no cost, the results are immediately available and no laboratory is necessary to develop or interpret the findings.
Stakeholder participation through citizen science
Citizen science and co-engaged action learning (Bonney et al., 2009;Pocock, et al., 2014;O'Donoghue et al., 2018) are, however, showing the way to more inclusive, enabling and effective social change processes. This work deepens the understanding of water issues in a practical and applied manner and enables actions for more sustainable practices (Graham & Taylor, 2018). Here the democratization of science engages people who often become proud and eager participants in building understanding and working for more sustainable practices rather than being the passive recipients of knowledge from others.
For challenges as complex as water management and ecological infrastructure 3 , the importance of context and the involvement of those participating is crucial. Many of these issues and problems require the integration of knowledge from the natural and social sciences, as well as economics, and there is rarely a single 'silver bullet' solution. As Bhaskar et al. (2010) states, 'exemplifying the triangular relationship of critical realism, interdisciplinarity and complex (open-systemic) phenomena' is needed for the investigation of such wicked problems as water resources management.
As stated above 'The democratisation of science, through citizen science processes, supported by practical and accessible 'tools of science,' is one area of work that is showing encouraging results' (Graham & Taylor, 2018, page V). Building collective capacity in the context of resource-based risks and uncertainty points towards the broad field of social learning (Wals, 2007) as a useful component of effective social change. These ideas and concepts form the basis of this paper which advocates an 'enabling' orientationrather than a traditional 'causal' approach (i.e. seeking to cause a change in others through top-down methodologies) (Taylor, 2014).
miniSASS, biomonitoring and Google Earth
We now explore miniSASS as a key enabling tool that may have global relevance in both mobilizing people, popularizing the Sustainable Development Goals (SDGs) and helping provide accessible biomonitoring data, at virtually no cost to the user, towards SDG indicator 6.3.2. This perspective on citizen science is mirrored in a seminal paper by Fritz et al. (2019) on citizen science and the United Nations SDGs. In their paper, Fritz et al. develop a road-map on how citizen science can support the SDGs. In keeping with this theme, we are exploring miniSASS as a complementary, citizen science orientated, research tool.
What is the stream assessment scoring system (miniSASS)?
miniSASS is a simple tool which can be used by anyone to monitor the health of a river. One simply collects a sample of macroinvertebrates (small organisms large enough to be seen with the naked eye) from a natural river or stream, and depending on which groups are present, one can calculate a River Health Index for the river. This score helps classify the health, or ecological condition of the river, ranging across five categories from natural (blue) to very poor (purple). The results can then be recorded on the miniSASS website Google Earth layer (www.minisass.org). This database is effectively a 'Living data' system where further data can continuously be added. Through miniSASS, one can learn about rivers, monitor their water quality, explore the drivers of water quality deterioration, and, of course, take action to improve the quality of the streams and rivers.
Challenges to be considered when applying miniSASS
As with any scientific enquiry processes, a number of challenges must be addressed when applying miniSASS, these include: • Participants must locate a local stream or river and be prepared to go into the water to locate the organisms. • The organisms are not always easy to catch for identification purposes. A small net, such as one used for a goldfish pond, can be helpful here.
• Once collected, the organisms need to be identified. This is not always easy. The miniSASS website, at www. minisass.org, does, however, provide a simple dichotomous key through which the users can key-out the organism they are seeking to identify.
• In any citizen science, endeavour issues of scientific accuracy are a concern. By offering people training courses in miniSASS, this issue is alleviated to some extent. Training can be undertaken online using a simple, instructional video from the miniSASS website referred to above. The validity of the data will be taken up further in the Results and Discussion section.
Where did miniSASS come from?
miniSASS (Graham et al., 2004) was derived from the more rigorous South African Scoring System (SASS), a biomonitoring method for evaluating river health (Dickens & Graham, 2002;Dallas & Day, 2004). The SASS method requires the ability to identify up to 90 different aquatic invertebrate families and thus a high level of training is required. There was, therefore, a need for a simpler, more user-friendly tool for biomonitoring that would still yield reliable water quality/river health data. This need gave rise to the development of miniSASS. The development process involved reducing the taxonomic complexity of SASS by creating broad groupings of invertebrates that could act as surrogates for the complete suite of SASS taxa. A rigorous statistical evaluation of a large volume of data from the SASS method was conducted in order to determine whether the miniSASS method would yield viable results, similar to those derived from SASS. This evaluation assessed data collected over a wide geographic and water quality range and provided indications that miniSASS is suitable for predicting SASS scores and is thus an appropriate indicator of biological water quality (Graham et al., 2004).
The strength of miniSASS has been evident for several years. Its use is widely applied in South Africa, where it was initially developed, although it has been successfully used in many other southern African countries. It has been effectively applied in India (in the Himalaya mountains at over 18,000 feet in altitude), in Vietnam, Canada (where the ambient air temperature was À20°C), Germany and Brazil. GroundTruth, an environmental engineering company, verifies the incoming data and has worked with the Water Research Commission to support this development through the www.minisass.org website. A topical feature of this website is the number of recent additions of data, as shown on the right-hand side of the screen. miniSASS is also found on the Water Research Commission's website www.wrc.org.za.
RESULTS AND DISCUSSION
The existing and future potential of miniSASS as a global citizen science monitoring tool suitable for SDG 6.3.2 Substantial development of miniSASS has taken place since its early inception. This work includes the development of an online portal, or website described above, that allows participants, ranging from school children to NGOs and other organizations, to upload their self-collected data. Although there may be concern about the validity of these data, largely due to a lack of training of those collecting it, this concern is offset by the fact that the data are 'crowd-sourced', allowing for the shear bulk of evidence to tell a valid story, perhaps even more reliably than the more sparsely collected 'official' data. Holt et al. (2013) describe and demonstrate the potential of citizen science data. They show that, despite biases, it is possible to statistically clean citizen science data so that it matches the quality of professional sampled data. Citizen-derived data can also cover huge geographical regions, whereas professionals can only cover small areas (due to the cost).
How universal is miniSASS?
Because many macroinvertebrates have part of their life cycle in the water and part in the air, they have been able to move vast distances, carried by water, wind and by ducks and other vectors, and are thus found spread across the world 4 . However, others, such as some crustaceans, have not moved so far and tend to be more confined. For this reason, macroinvertebrate samples collected across the world have many similarities, especially at the taxonomic level of order or family, while at a local level, there is plenty of division into local genera and species. For this reason, indices that are based on the higher taxonomic level of order and family are more globally applicable. This was validated, in South Africa, and was a large part of the success of the SASS index (Dickens & Graham, 2002) which is based largely on family identification, making the index inexpensive and thus affordable for routine and large-scale monitoring.
An index that is to be applied at a global level could be improved with local adaptations. This can be done, not only to add or subtract orders or families but also to verify the sensitivity of the groups. Such adaptation could be done at an 'eco-region' level, for example, all northern cold-water European countries are likely to have similar invertebrates, which will need to be separated from the African ones which will also be separate from the Asian ones. We are finding that the differences are relatively minor, however, and a single index that includes the orders and families most important for ALL regions of the world, is viable as a citizen science instrument. A generalized and indicative global index, using the miniSASS methodology, is thus possible for citizen scientists.
miniSASS has many strengths, as well as a number of challenges. These are tabulated in Table 1.
A summary of SDG indicator 6.3.2 methodology SDG indicator 6.3.2 is reported by countries as the proportion of bodies of water with good ambient water quality. It is one of two indicators of Target 6.3 which aims to improve the quality of water in rivers, lakes and groundwaters by reducing pollution. Level one monitoring of the official indicator methodology (UN Water, 2018) relies on water quality data from in situ measurements and the analysis of samples collected from rivers, lakes and aquifers. Water quality is assessed by measuring physical and chemical parameters that reflect natural water quality, together with major human impacts on water quality. Level two reporting can include any type of water quality data that can be used to classify a body of water. Examples include data from citizen initiatives, Earth observation products, biological approaches or additional water quality parameters are not included in the core Level one list. The indicator methodology stipulates that countries are divided into river basin-based reporting districts, which are further divided into smaller water body units. These small hydrologically defined units are classified based on the results of measurements of five core parameter groups: oxygen, salinity, nitrogen, phosphorus and acidification. These data are compared to numerical target values, and if a compliance rate of 80% or more is achieved, a water body is classified as having 'good' ambient water quality.
Case study: using miniSASS data to generate an SDG indicator 6.3.2 score In many parts of the world, there are significant data gaps, both spatially and temporally, in the water quality record which cannot be filled using 'conventional monitoring programmes'. Citizen science projects are one of several approaches currently being explored to see whether they can play a significant role in filling these data gaps.
The miniSASS data generated by citizens do not fit the requirements of Level one reporting for SDG indicator 6.3.2 as they are based on a biological assessment, rather than physico-chemical data collection, and are not sampled at fixed monitoring locations. In this study, an indicator 6.3.2 score was generated that could be described as a 'Level two report' based on the current methodology ( UN Water, 2018).
In order to calculate an indicator score, a data-rich area was selected as shown in Figure 1. The Department of Water and Sanitation of South Africa defines drainage basins for water resource management purposes. The case study area aligns with Drainage Basin U. River water bodies were defined using the HydroATLAS Level 10 units (Lehner & Grill, 2013) and a total of 129 river water body units were defined for the drainage basin. Each min-iSASS data record was allocated to a water body unit based on spatial location, and the scores compared to the Fair/Good boundary of the ecological categories for the two river types (!5.9 for sandy-type rivers and !6.2 for rocky-type rivers). A water body was classified as 'good' if 80% of samples met this target.
In order to calculate the SDG indicator score, the proportion of water bodies within the basin with good water quality were calculated. Of the 129 river water bodies defined, 40 had miniSASS monitoring data and 6 of these were classified as 'good'. This thus yielded an SDG indicator score of 15 for this basin (6/40*100 ¼ 15).
Strengths Challenges
It supports the global trend to engage citizen science. This is especially relevant for realizing SDG 6 (b). Crowd-sourced data have its own unique validity; while each sample may not have a high level of confidence, the sheer number of data records strengthens the research rigor. The approach engages citizens with the SDG agenda, enabling them to contribute to a global effort. This could become a VERY big promotion for the SDGs. miniSASS data have been used to demonstrate citizen science participation in monitoring compliance with water quality objectives. The miniSASS data management system allows for the clustering of the data into a time-series. This means progress over time can be measured and compared at the same site. miniSASS costs very little to use. Simple apparatus such as a net, which can be home-made, and a reference sheet that is available as a free down-load, on the website, strengthens the miniSASS study. Since the macroinvertebrates are visible to the naked eye, the shape and form are of most importance. This means that advanced competence in languages such as English is not essential. Indeed, nine-year-old isiZulu speaking children are able to master the technique. miniSASS materials are also available in other languages such as French, Afrikaans and isiZulu.
Participants need to learn how to do miniSASS. Although there are simple instructions and tutorials on the website, participants learn best in the field with an experienced person. Citizen science by nature requires a level of coordination. At present, the coordination is provided by Ayanda Lepheana and GroundTruth with website support from SAIAB a and SAEON b , both South African government-supported institutions. If the miniSASS data are to be used for SDG reporting globally, it will require additional support. Approval of data by the government may be challenging if the government prefers to 'be in charge' and not receptive to citizen science input and participation. To what extent will governments embrace and support the democratization of science? Each country will have the ability to either embrace citizen science to its fullest, or for government officials to use the method themselves as a low-tech monitoring method. While the latter is not invalid, it is unlikely that it will result in the high number of data that will be collected by a strong citizen science programme.
Corrected Proof
One key finding of this analysis was that the monitoring effort differed considerably between water bodies. The most data records for any single water body were 183, whereas several had only a single record. This disparity in monitoring effort results in some water bodies being classified with a much higher degree of confidence compared to others. A further development of this method could include specifying a minimum data requirement to ensure that water bodies are classified equally and reliably. In this example, setting a minimum data requirement of five monitoring records per water body resulted in 17 water bodies being monitored, none of which were classified as 'good'. In addition to defining minimum data requirements, future testing could include optimizing monitoring network design to improve data collection coverage.
miniSASS as a proxy for formal water quality monitoring programmes
Much of the strength of miniSASS lies in its ability to generate large amounts of data through citizen science and crowdsourcing. Although these data may not always be entirely valid, due to the fact that many of the people who collect it may not have received formal training, it has its own unique validity as the sheer number of data records strengthens rigour (Holt, et al., 2013). In order to assess the ability of miniSASS to act as a proxy for formal water quality monitoring programmes, miniSASS data were compared against data collected by the River Ecostatus Monitoring Programme (REMP). The REMP assesses the ecological condition of South Africa's rivers based on a rapid assessment of aquatic macroinvertebrates, using the Macroinvertebrate Response Assessment Index (MIRAI).
Corrected Proof
The 2017/2018 REMP data were compared against the miniSASS data collected for the same time period. In 2017 and 2018, a total of 522 miniSASS data entries (234 and 288 in each year, respectively) were recorded across South Africa. Of these, 13 were recorded within a 500 m radius of a REMP monitoring point and 98 within a 5 km radius ( Figure 2). However, only 28 REMP sites within 5 km of miniSASS sampling points and 11 within 500 m of miniSASS sampling points had REMP data recorded during this time. Of the 11 miniSASS entries recorded within 500 m of REMP monitoring sites, four yielded the same ecological category as those reported at the REMP sites, three yielded an ecological category one category below those reported at the REMP sites, and the remaining four yielded ecological categories two categories below those reported at the REMP sites. The frequency of samples recorded in each ecological category by the REMP and miniSASS data collection is presented in Table 2.
Although the results assessed here do not provide conclusive evidence of the relationship between miniSASS and REMP data, they provide some indication that miniSASS is able to yield results similar to those derived from the REMP, particularly for rivers in a lower ecological condition (C, D and E). This, in combination with the fact that the method has been extensively assessed against SASS data and is strongly rooted in rigorous statistical evaluations, suggests that, where rigorous data collection may not be feasible due to resource constraints, mini-SASS can provide defensible water quality results. Considering that many of South Africa's rivers are in a degraded state, a citizen science tool that can be used to provide evidence of a river's degraded state and draw attention to the plight of the freshwater resources, is of immense value. Only samples collected at miniSASS and REMP sampling points within 500 m of each other are displayed. |
Quantitation of Acetyl Hexapeptide-8 in Cosmetics by Hydrophilic Interaction Liquid Chromatography Coupled to Photo Diode Array Detection
: Bioactive peptides are gaining more and more popularity in the research and development of cosmetic products with anti-aging effect. Acetyl hexapeptide-8 is a hydrophilic peptide incorporated in cosmetics to reduce the under-eye wrinkles and the forehead furrows. Hydrophilic interaction liquid chromatography (HILIC) is the separation technique of choice for analyzing peptides. In this work, a rapid HILIC method coupled to photodiode array detection operated at 214 nm was developed, validated and used to determine acetyl-hexapeptide-8 in cosmetics. Chromatography was performed on a Xbridge ® HILIC BEH analytical column using as mobile phase a 40 mM ammonium formate water solution (pH 6.5)-acetonitrile mixture 30:70, v/v at flow rate 0.25 mL min − 1 . The assay was linear over the concentration range 20 to 30 µ g mL − 1 for the cosmetic formulations and 0.004 to 0.007% ( w/w ) for the cosmetic cream. The limits of quantitation for acetyl hexapeptide-8 were 1.5 µ g mL − 1 and 0.002% ( w/w ) for the assay of cosmetic formulations and cosmetic creams, respectively. The method was applied to the analysis of cosmetic formulations and anti-wrinkle cosmetic creams.
Introduction
Skin aging is a biological process influenced by various genetic, environmental (pollution, UV radiation), hormonal and metabolic factors. For more than 20 years, bioactive ingredients have been incorporated in cosmetics to smooth out deep wrinkles, improve skin elasticity and reduce the effects of the skin aging [1]. Given that most natural processes within the body are stimulated through the interaction of peptides and proteins with their target partners, bioactive peptides incorporated in cosmetics are one of the most popular ways to reduce wrinkles and fine lines, improve skin appearance and texture, and treat decolorated skin [2]. The role of peptides is crucial in several natural processes related to skin care, such as the modulation of cell proliferation, inflammation, melanogenesis, cell migration, angiogenesis and the synthesis and regulation of proteins. Bioactive peptides are gaining more and more popularity in the research and development of cosmetic products with anti-aging effect [3]. Acetyl hexapeptide-8, also known as acetylhexapeptide-3, is a neurotransmitter inhibitor peptide designed from the N-terminal end of the synaptosomal-associated protein (SNAP25) [4,5]. It competitive inhibits the SNAP25 component of the said vesicle docking and fusion protein complex (SNARE) [6] which triggers the calcium-dependent neurotransmitter release into the synapse, a process necessary for muscle contraction [7][8][9][10]. Acetyl hexapeptide-8 is marketed as Argireline ® [11], and it has been efficiently used in cosmetics for smoothening the under-eye wrinkles and the forehead furrows [12][13][14]. After topical application at specific areas of the face, it inhibits the reactions that cause muscles to move or contract for example when forming facial expressions such as smiling or frowning [15,16]. A clinical trial of daily topical application of acetyl hexapeptide-8 in 24 patients with blepharospasm concluded that topical application of this peptide is safe and promising for prolonging the action of injectable botulinum neurotoxin therapy [17]. The quality control of cosmetic products containing bioactive peptides should be addressed under a more systematic investigation and the concentration of these peptides in cosmetics should be supported by product-specific studies. Therefore, there is a real need to set up analytical methods to quantitate the bioactive compounds in cosmetic products.
In the last decade, the increased interest in the separation of peptides has gained momentum due to the emphasis on the chromatographic separation of various proteins in proteome. High performance liquid chromatography (HPLC) has been widely used in the analysis of peptides in various fields of research and development, using different modes of separation. Nowadays, hydrophilic interaction liquid chromatography is the separation technique of choice for the analysis of peptides [18][19][20][21][22]. Usually, bioactive peptides incorporated in cosmetic products are hydrophilic compounds that show little or no retention on conventional RP-HPLC analytical columns. The stationary phases in HILIC are mainly polar such as silica gel, diol-, amino-or cyano-bonded and other zwitterionic packing materials and the typical mobile phases consists of mixtures of a highly polar solvent (typically water) with an organic modifier (typically acetonitrile) [23,24]. The analytes retention is increased by increasing the proportion of the organic modifier in the mobile phase [25,26]. The polar functional groups on the HILIC stationary phases absorb water (0.5%-1.0%) and this way a water-enriched layer is immobilized between the mobile and the stationary phase, especially when the water content of the mobile phase is less than 40% [27]. In HILIC the more hydrophilic analytes are eluted later than the less polar compound. In the literature several works have been published on peptide separation using HILIC columns [28][29][30], but only a few studies were dedicated to peptide quantitation in cosmetics [31][32][33]. In one of these publications, ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) using a TSK-gel Amide-80 ® HILIC analytical column was used to quantitate acetyl hexapeptide-8 in cosmetics after solid phase extraction procedure [34]. The TSK-gel Amide-80 ® HILIC analytical column was also used in LC-MS/MS methods developed to evaluate transdermal absorption of acetyl-hexapeptide-8 [35,36]. Even though the abovementioned LC-MS/MS approaches are selective and sensitive for the quantitation of acetyl-hexapeptide-8 in various matrices, there is a real need for the development of a reliable analytical method without the need for specialized equipment that can be used in routine analyses.
In this work a rapid and sensitive hydrophilic interaction liquid chromatographic method with photodiode array (PDA) detection was developed and validated for the quantitation of acetyl-hexapeptide-8 in cosmetics. The appropriate stationary phase, pH, buffer concentration and mobile phase composition, was thoroughly investigated prior to method validation. The combination of HILIC with PDA detection provides an accurate, repeatable and robust method for the quantitative analysis of cosmetic products. To the best of our knowledge, this is the first report of a HILIC-PDA method for the quantitation of acetyl-hexapeptide-8 in cosmetics. In this work a Xbridge ® -HILIC BEH analytical column has been used and combined with a rapid and simple sample pretreatment. All the above in combination with a short run time of less than 10 min, makes the proposed HILIC-PDA method suitable for the routine quality control of cosmetics.
Chemical and Reagents
HPLC grade solvents were bought from Sigma-Aldrich (St. Louis, MO, USA). Analytical reagent grade ammonium formate was acquired from Alfa-Aesar (Haverhill, MA, USA). HPLC grade water was produced by means of a Synergy ® UV water purification system (Merck Millipore, MA, USA). Whatman nylon membrane filters with pore size 0.45 µm and diameter 47 mm were purchased from GelmanSciences (Northampton, UK). Hydrophobic polytetrafluorethylene (PTFE phobic 13 mm, pore size 0.22 µm) syringe filters were acquired from Novalab SA, Athens, Greece representative of RephiLe Bioscience Ltd., Europe.
The anti-wrinkle cosmetic cream containing 0.005% w/w acetyl hexapeptide-8 was produced in the Laboratory of Chemistry-Biochemistry-Cosmetic Science, Department of Biomedical Sciences, University of West Attica in Athens, Greece by using the Argireline peptide solution C ® . The excipients present in anti-wrinkle cream are aqua, xalifin-15, propylene glycol, sabowax FX-65, squalene, butylated hydroxyl toluene (BHT) and germall 115. Placebo cream containing only the excipients, without acetyl hexapeptide-8, was also prepared for validation purposes.
Stock and Calibration Standard Solutions
Acetyl hexapeptide-8 stock standard solution at 500 µg mL −1 was prepared in acetonitrile-water mixture (60:40, v/v). The stock standard solution was further diluted in acetonitrilewater mixture (60:40, v/v) to prepare mixed working standard solutions. The solutions were stored in amber bottles at 4 • C and remained stable for two months.
For the quantitation of acetyl hexapeptide-8 in the anti-wrinkle cosmetic cream the calibration spiked cream samples at concentration levels 0.004, 0.0045, 0.005, 0.006 and 0.007 w/w were prepared by spiking placebo cream with appropriate dilutions of acetyl hexapeptide-8 stock standard solution. Quality control (QC) samples were also prepared in a similar manner at concentration levels 0.004, 0.005 and 0.007% w/w.
Cosmetic Formulation
An accurately weighted amount (0.5 g) of Argireline peptide solution C ® is transferred at a 10 mL volumetric flask and diluted to volume with water/acetonitrile (30:70, v/v). A portion of this solution is then analyzed by the proposed HILIC-PDA method for the quantitation of acetyl hexapeptide-8.
Cosmetic Cream
An accurately weighted amount (0.1 g) of cosmetic cream is mixed with 200 µL of acetonitrile-water mixture (60:40, v/v) and 800 µL of 30% 40 mM ammonium formate water solution in acetonitrile. The mixture is shaken for 2 min and then centrifuged at 18,000× g for 30 min, at ambient temperature. The upper layer is then filtered through a PTFE hydrophobic syringe filter prior to HILIC-PDA analysis.
HILIC-PDA
The HPLC-PDA analytical instrument used in this work is consisting of a Waters 717 plus autosampler, a column temperature oven, a Waters 1515 isocratic pump and a Waters 996 photodiode array detector (Milford, MA, USA). The Empower software (Milford, MA, USA) was used for the data acquisition. The chromatographic eluent was monitored over the wavelengths 200 to 400 nm and extracted chromatograms at λ 214 nm were used for data analysis. An Xbridge ® -HILIC BEH guard column (20 × 2.1 mm, 3.5 µm) in line with an Xbridge ® -HILIC BEH analytical column (2.1 × 150 mm, 3.5 µm) were used for the chromatography. The mobile phase was composed of 30% 40 mM ammonium formate aqueous solution in acetonitrile and pumped at a flow rate of 0.25 mL min −1 . Prior to the chromatography the mobile phase was filtered through a 0.22 µm nylon membrane filter, Membrane Solutions (Kent, WA, USA) and degassed under vacuum. Samples were injected via a 10 µL injection loop and acetyl hexapeptide-8 was quantitated in cosmetic products with a chromatographic run time of 10 min.
Method Validation and Application to the Analysis of Real Samples
The HILIC-PDA method was validated in terms of linearity, limit of detection, limit of quantitation, intra-day and inter-day precision and overall accuracy [37]. The method was applied to the analysis of various batches of a cosmetic formulation namely Argireline peptide solution C ® and to the analysis of various batches of an anti-wrinkle cosmetic cream. To evaluate the linearity, linear regressions were used to construct the calibration graphs after the analysis calibration standards and spiked cream samples at five different concentration levels. Peak area measurements were used for quantitation of acetyl hexapeptide-8. The % coefficient of variations (%CVs) and the % relative recovery were calculated to evaluate precision (intra-and inter-day) and overall accuracy, respectively.
HILIC-PDA Method Development Chromatography
Acetyl-hexapeptide-8 consists of a six amino acids chain acetylated at the N-terminal residue, N-acetyl-Glu-Glu-Met-Gln-Arg-ArgNH 2 , as shown in Figure 1a
HILIC-PDA
The HPLC-PDA analytical instrument used in this work is consisting of a Waters 717 plus autosampler, a column temperature oven, a Waters 1515 isocratic pump and a Waters 996 photodiode array detector (Milford, MA, USA). The Empower software (Milford, MA, USA) was used for the data acquisition. The chromatographic eluent was monitored over the wavelengths 200 to 400 nm and extracted chromatograms at λ 214 nm were used for data analysis. An Xbridge ® -HILIC BEH guard column (20 × 2.1 mm, 3.5 µ m) in line with an Xbridge ® -HILIC BEH analytical column (2.1 × 150 mm, 3.5 μm) were used for the chromatography. The mobile phase was composed of 30% 40 mM ammonium formate aqueous solution in acetonitrile and pumped at a flow rate of 0.25 mL min −1 . Prior to the chromatography the mobile phase was filtered through a 0.22 µ m nylon membrane filter, Membrane Solutions (Kent, WA, USA) and degassed under vacuum. Samples were injected via a 10 µ L injection loop and acetyl hexapeptide-8 was quantitated in cosmetic products with a chromatographic run time of 10 min.
Method Validation and Application to the Analysis of Real Samples
The HILIC-PDA method was validated in terms of linearity, limit of detection, limit of quantitation, intra-day and inter-day precision and overall accuracy [37]. The method was applied to the analysis of various batches of a cosmetic formulation namely Argireline peptide solution C ® and to the analysis of various batches of an anti-wrinkle cosmetic cream. To evaluate the linearity, linear regressions were used to construct the calibration graphs after the analysis calibration standards and spiked cream samples at five different concentration levels. Peak area measurements were used for quantitation of acetyl hexapeptide-8. The % coefficient of variations (%CVs) and the % relative recovery were calculated to evaluate precision (intra-and inter-day) and overall accuracy, respectively. LogD values of acetyl hexapeptide-8 versus pH are less than -9, indicating that this compound is highly hydrophilic (Figure 1b, bottom). HILIC is the analytical technique of LogD values of acetyl hexapeptide-8 versus pH are less than -9, indicating that this compound is highly hydrophilic (Figure 1b, bottom). HILIC is the analytical technique of choice for the chromatographic analysis of polar compounds, and it was therefore used in the present work. The retention mechanism in HILIC is based on several types of interactions such as adsorption, partition, electrostatic, hydrogen bonding and reversed-phase interactions [38][39][40]. Greater retention is achieved when more than 70% of organic modifier (e.g., acetonitrile) is used in the mobile phase. The chromatographic conditions were optimized to achieve adequate retention and optimum peak shape of acetyl-hexapeptide-8.
HILIC-PDA Method Development
To find the optimal mobile phase composition we examined various combinations of aqueous buffer solutions and acetonitrile with changed content of each component. The detection wavelength was set to 214 nm, because at this wavelength acetyl heptpeptide-8 shows satisfactory absorption. The flow rate was set to 0.25 mL min −1 and the experiments were conducted at ambient temperature.
The XBridge ® -HILIC BEH analytical column used in this work consists of BEH particles. Some accessible free silanol groups on the surface of these BEH particles are responsible for electrostatic interactions. The addition of aqueous salt solutions in the HILIC mobile phase eluents reduces the electrostatic interactions between the stationary phase and the analyte [41]. Plot of the logk values of acetyl hexapeptide-8 as a function of the concentration of ammonium formate is presented in Figure 2a. Ammonium formate concentration was modified from 2.5 to 100 mM with a constant aqueous component of the mobile phase eluent at 30%, v/v and a constant pH at 6.5. Under these conditions the free silanol groups on the surface of these BEH particles are negatively charged and acetyl hexapeptide-8 is in zwitterion form. The results showed that by increasing the concentration of ammonium formate the retention of acetyl hexapeptide-8 is slightly decreased up to 40 mM and then increased up to 100 mM. These findings indicate that the retention mechanism of acetyl hexapeptide-8 in XBridge ® -HILIC BEH analytical column is complex and comprises both hydrophilic partition with secondary electrostatic interactions. From these experiments, we concluded that by using a 40 mM ammonium formate concentration in the mobile phase peak symmetry and plate numbers are improved and the analyte is adequately retained and well separated from the solvent front.
choice for the chromatographic analysis of polar compounds, and it was therefore used in the present work. The retention mechanism in HILIC is based on several types of interactions such as adsorption, partition, electrostatic, hydrogen bonding and reversed-phase interactions [38][39][40]. Greater retention is achieved when more than 70% of organic modifier (e.g., acetonitrile) is used in the mobile phase. The chromatographic conditions were optimized to achieve adequate retention and optimum peak shape of acetyl-hexapeptide-8. To find the optimal mobile phase composition we examined various combinations of aqueous buffer solutions and acetonitrile with changed content of each component. The detection wavelength was set to 214 nm, because at this wavelength acetyl heptpeptide-8 shows satisfactory absorption. The flow rate was set to 0.25 mL min −1 and the experiments were conducted at ambient temperature.
The ΧBridge ® -HILIC ΒΕΗ analytical column used in this work consists of BEH particles. Some accessible free silanol groups on the surface of these BEH particles are responsible for electrostatic interactions. The addition of aqueous salt solutions in the HILIC mobile phase eluents reduces the electrostatic interactions between the stationary phase and the analyte [41]. Plot of the logk values of acetyl hexapeptide-8 as a function of the concentration of ammonium formate is presented in Figure 2a. Ammonium formate concentration was modified from 2.5 to 100 mM with a constant aqueous component of the mobile phase eluent at 30%, v/v and a constant pH at 6.5. Under these conditions the free silanol groups on the surface of these BEH particles are negatively charged and acetyl hexapeptide-8 is in zwitterion form. The results showed that by increasing the concentration of ammonium formate the retention of acetyl hexapeptide-8 is slightly decreased up to 40 mM and then increased up to 100 mM. These findings indicate that the retention mechanism of acetyl hexapeptide-8 in ΧBridge ® -HILIC ΒΕΗ analytical column is complex and comprises both hydrophilic partition with secondary electrostatic interactions. From these experiments, we concluded that by using a 40 mM ammonium formate concentration in the mobile phase peak symmetry and plate numbers are improved and the analyte is adequately retained and well separated from the solvent front. The chromatography of acetyl hexapeptide-8 was also explored by using various mobile phases where the concentration of ammonium formate in the whole mobile phase was kept constant at 12 mM, while the percentage of water, Φwater varied from 25% to 35%. As shown in Figure 2b, the logk values of the peptide decrease exponentially with increasing Φwater, implying a complex retention mechanism for this analyte on the selected HILIC column. The optimum mobile phase composition consists of 30% 40 mM ammonium formate water solution (pH 6.5) in acetonitrile. As shown in Figure 3, acetyl hexapeptide-8 is eluted at 8.15 min and the proposed HILIC-PDA method allows the isocratic elution of acetyl hexapeptide-8 within 10 min. The chromatography of acetyl hexapeptide-8 was also explored by using various mobile phases where the concentration of ammonium formate in the whole mobile phase was kept constant at 12 mM, while the percentage of water, Φ water varied from 25% to 35%. As shown in Figure 2b, the logk values of the peptide decrease exponentially with increasing Φ water , implying a complex retention mechanism for this analyte on the selected HILIC column. The optimum mobile phase composition consists of 30% 40 mM ammonium formate water solution (pH 6.5) in acetonitrile. As shown in Figure 3, acetyl hexapeptide-8 is eluted at 8.15 min and the proposed HILIC-PDA method allows the isocratic elution of acetyl hexapeptide-8 within 10 min.
Selectivity
The selectivity of the HILIC-PDA method to the analysis of Argireline peptide solution C ® (cosmetic formulation) is demonstrated in Figure 4, where a chromatogram obtained from the analysis of the cosmetic formulation (red spiked line) is superimposed to a chromatogram of a quality control sample of acetyl hexapeptide-8 prepared in water/acetonitrile (30:70, v/v), both samples contain the analyte at 25 μg mL −1 (grey line). Moreover, the selectivity of the HILIC-PDA method to the analysis of cosmetic creams incorporated with acetyl hexapeptide-8 is demonstrated in Figure 5, where a chromatogram obtained from the analysis of a placebo cream sample (black line) is superimposed to a chromatogram of a cream sample obtained after the sample preparation described in Section 2.3.2 containing acetyl hexapeptide-8 at 0.005% w/w (blue line).
Selectivity
The selectivity of the HILIC-PDA method to the analysis of Argireline peptide solution C ® (cosmetic formulation) is demonstrated in Figure 4, where a chromatogram obtained from the analysis of the cosmetic formulation (red spiked line) is superimposed to a chromatogram of a quality control sample of acetyl hexapeptide-8 prepared in water/acetonitrile (30:70, v/v), both samples contain the analyte at 25 µg mL −1 (grey line).
Selectivity
The selectivity of the HILIC-PDA method to the analysis of Argireline peptide solution C ® (cosmetic formulation) is demonstrated in Figure 4, where a chromatogram obtained from the analysis of the cosmetic formulation (red spiked line) is superimposed to a chromatogram of a quality control sample of acetyl hexapeptide-8 prepared in water/acetonitrile (30:70, v/v), both samples contain the analyte at 25 μg mL −1 (grey line). Moreover, the selectivity of the HILIC-PDA method to the analysis of cosmetic creams incorporated with acetyl hexapeptide-8 is demonstrated in Figure 5, where a chromatogram obtained from the analysis of a placebo cream sample (black line) is superimposed to a chromatogram of a cream sample obtained after the sample preparation described in Section 2.3.2 containing acetyl hexapeptide-8 at 0.005% w/w (blue line).
Linearity Data
For the quantitation of acetyl hexapeptide-8 in the cosmetic formulation (Argireline peptide solution C ® ) the calibration curves have been constructed at the range of concentrations 20 to 30 μg mL −1 . The peak area signal of the peptide, S, versus the corresponding concentrations, C exhibited linear relationships and the results of a typical calibration curve are shown in Table 1. A Student's t-test was also performed to evaluate whether the intercept of the regression equation was significantly different from the theoretical zero value. The test was based on the estimation of the experimental t-value, texperimental = a/Sa, where a is the intercept and Sa is the standard deviation of the intercept of the regression equation, and on the comparison of texperimental with the theoretical t-value. tp. The results presented in Table 1 indicate that the intercept of the regression equation does not differ from the theoretical zero value.
Linearity Data
For the quantitation of acetyl hexapeptide-8 in the cosmetic formulation (Argireline peptide solution C ® ) the calibration curves have been constructed at the range of concentrations 20 to 30 µg mL −1 . The peak area signal of the peptide, S, versus the corresponding concentrations, C exhibited linear relationships and the results of a typical calibration curve are shown in Table 1. A Student's t-test was also performed to evaluate whether the intercept of the regression equation was significantly different from the theoretical zero value. The test was based on the estimation of the experimental t-value, t experimental = a/Sa, where a is the intercept and Sa is the standard deviation of the intercept of the regression equation, and on the comparison of t experimental with the theoretical t-value. tp. The results presented in Table 1 indicate that the intercept of the regression equation does not differ from the theoretical zero value. For the quantitation of acetyl hexapeptide-8 in cosmetic creams, calibration curves were constructed after the analysis of spiked cream samples over the concentration range 0.004 to 0.007 w/w. The results of a typical calibration curve are presented in Table 2. In all cases correlation coefficient is greater than 0.994 indicating linear relationships between the peak area signal of the analyte, S and the corresponding concentrations, C. A Student's t-test was also performed in analogous manner, and the results ( Table 2) indicate that the intercept of the regression line is not significantly different from zero and thus there is no interference from the cream matrix. Limit of detection (LOD) and limit of quantitation (LOQ) values for acetyl hexapeptide-8 were calculated as the amounts for which the signal-to-noise ratios were 3:1 and 10:1, respectively. This was achieved by the analysis of dilute solutions of the peptide at known concentration prepared by the appropriate sample preparation procedure [42]. LOD and LOQ values for acetyl hexapeptide-8 in cosmetic formulation and in cosmetic cream are reported in Table 1 and in Table 2, respectively.
Accuracy and Precision
Precision and accuracy were evaluated by one-way analysis of variance (ANOVA) and the results are presented in Table 3. The total precision was between 1.74 to 4.34 for the cosmetic formulation and 2.46 to 3.53% for acetyl hexapeptide-8 in cosmetic cream. The total accuracy was between 98.9 to 99.8% for the analyte in cosmetic formulation and 99.3 to 101.6% for the quantitation in cosmetic cream. Table 3. Accuracy and precision data of the HILIC-PDA method for the quantitation of acetyl hexapeptide-8 in cosmetic formulation and cosmetic creams (n = 3 runs in 5 replicates).
Matrix
Concentration Levels
Cosmetic Formulation
Added
Application to the Analysis of Real Samples
The proposed method was applied to the analysis of three batches of Argireline peptide solution C ® labelled to contain 0.05% w/w acetyl hexapeptide-8, and three batches of anti-wrinkle cosmetic cream labelled to contain 0.005% w/w of the peptide. Results obtained from the analysis of real cosmetic products are presented in Table 4. The % recovery for the quantitation of acetyl hexapeptide-8 by the proposed HILIC-PDA method is ranged from 98.2 to 102.2 % in cosmetic formulation and from 98.2 to 101.8% in cosmetics creams.
Conclusions
There is a real need to set up analytical methods to quantitate the active compounds in cosmetic products incorporated with bioactive peptides in low content. In this work, a HILIC-PDA method was developed and validated for the determination of acetyl hexapeptide-8 in cosmetics. Over the past two decades the use of biopeptides in cosmetic products is increasingly expanded. The developed method takes full advantage of the benefits of HILIC leading to efficient retention of acetyl hexapeptide-8 with less matrix effect. Validation results demonstrate that the proposed method allows for the quantitation of acetyl hexapeptide-8 in both cosmetic formulations and cosmetics creams. The simplicity of sample preparation procedure and the short chromatographic run time of less than 10 min gives the method the capability for high sample throughput and it can be used to support quality control of cosmetic products containing low content of acetyl hexapeptide-8. There is no doubt that HILIC chromatography enables the determination of bioactive peptides in cosmetic products without the need for specialized detection methods. The proposed method could be extended for future applications in the analysis of various bioactive peptides used for cosmetic purposes. |
Multiple Gene Transfer and All-In-One Conditional Knockout Systems in Mouse Embryonic Stem Cells for Analysis of Gene Function
Mouse embryonic stem cells (ESCs) are powerful tools for functional analysis of stem cell-related genes; however, complex gene manipulations, such as locus-targeted introduction of multiple genes and conditional gene knockout conditional knockout, are technically difficult. Here, we review recent advances in technologies aimed at generating cKO clones in ESCs, including two new methods developed in our laboratory: the simultaneous or sequential integration of multiple genes system for introducing an unlimited number of gene cassettes into a specific chromosomal locus using reciprocal recombinases; and the all-in-one cKO system, which enables introduction of an EGFP reporter expression cassette and FLAG-tagged gene of interest under an endogenous promoter. In addition, methods developed in other laboratories, including conventional approaches to establishment of cKO cell clones, inducible Cas9-mediated cKO generation, and cKO assisted by reporter construct, invertible gene-trap cassette, and conditional protein degradation. Finally, we discuss the advantages of each approach, as well as the remaining issues and challenges.
INTRODUCTION
Gene knockout (KO) technology has made a substantial contribution to knowledge of gene function. KO mice and KO cells prepared from them are frequently used for analysis of gene function in mammalian cells; however, generation of KO mice requires extended periods of time and cumbersome processes, including isolation of gene-targeted mouse embryonic stem cell (ESC) clones, production of chimera mice carrying the KO ESCs, establishment of germline-transmitted heterozygous mice, and cross-breeding of the heterozygous mice. Preparation of genetically disrupted cells is an alternative approach for analysis of gene function in vivo; however, it is also challenging, due to the technical difficulties involved in gene targeting. Recent developments in genome editing technologies have addressed these issues and greatly accelerated the molecular analysis of gene function (Gaj et al., 2013;Gupta and Musunuru 2014). CRISPR/Cas9 is the most popular genome editing system because of its high efficiency and easy design/implementation. CRISPR/Cas9 generates a double strand break (DSB) at the target site, which is repaired by the errorprone non-homologous end joining (NHEJ) process, resulting in the introduction of insertion/ deletion mutations and consequent target gene disruption. CRISPR/Cas9-induced gene disruption is relatively efficient in mammalian cells and has greatly reduced the time and cost required for molecular analysis of gene function. Nevertheless, simple mutagenesis by genome editing technology is not suitable for analysis of lethal genes, which are essential for cell growth, survival, or maintenance of the undifferentiated status of stem cells. Gene knockdown with short interference RNA (siRNA or shRNA) is often applied in these cases; however, these knockdown systems often do not completely suppress target gene expression, which can lead to inconclusive results.
The conditional knockout (cKO) approach, first reported by Gu et al. (1994), is a useful way to study genes difficult to investigate using other approaches. cKO cells are usually generated using recombinases, such as Cre and FLP, in combination with their respective recognition sequences, loxP and FRT. The coding exon(s) of the target gene is/are flanked by these recognition sequences, and their corresponding recombinases are conditionally expressed to induce gene KO in specific cells. Definitive experimental results are expected, as the genetic disruption induces complete elimination of target gene expression. While cKO cells can represent an ideal option, their construction requires targeting of all alleles in each cell. Therefore, few cell lines are suitable for establishing cKO clones, March 2022 | Volume 10 | Article 870629 2 since most are hyperploid and exhibit low homologous recombination efficiency. To overcome these challenges, various cKO methods have been developed with the aid of genome editing technology. In this review, we provide an overview of recent advances in the development of cKO strategies, particularly the all-in-one cKO system, as well as their advantages and issues that need to be addressed.
CKO CELL ESTABLISHMENT USING A CONVENTIONAL STRATEGY
Mouse ESCs are useful for preparing cKO cells, since ESCs have a normal karyotype and relatively high homologous recombination rates compared with conventional cell lines. The functions of various genes involved in stemness, cell growth, and survival have been clarified using cKO ESCs (Dejosez et al., 2008;Dovey et al., 2010;Lu et al., 2014). The conventional procedure for preparation of cKO ESCs involves introduction of a targeting vector containing positive-selection marker genes (e.g., a neomycin resistance gene) flanked by FRT sites, a negative-selection marker (e.g., herpes simplex virus-derived thymidine kinase), and a coding exon (or exons) of the target gene, flanked by loxP sites, into ESCs ( Figure 1A). Targeted ESC clones can be isolated by positive-negative selection with 5-10% efficiency (Johnson et al., 1989). After isolation of a targeted clone, the positiveselection marker gene is removed by transient expression of FLP to retain normal expression of the target gene. These targeting processes are then repeated for the other allele. Therefore, a total of four cloning steps are required to establish cKO ESC clones. Due to this time-consuming process, establishment of cKO cells has not been a popular choice for analysis of gene function, despite its numerous advantages. Moreover, prolonged culture of ESCs for repeated cloning may compromise their undifferentiated characteristics. To avoid this concern, one could breed ESC-derived heterozygous mice, although this procedure requires much longer time. Dow et al. (2015) reported a cKO system based on CRISPR/ Cas9-induced gene disruption ( Figure 1B). To enable conditional knockout of the target gene, a guide RNA expression cassette and doxycycline (Dox)-inducible Cas9 cassette were inserted to the safe harbor locus (genetically reliable locus), Col1a1, of ESCs stably expressing reverse tetracycline transactivator (rtTA). Using this system, approximately 70% of cells displayed biallelic frame-shift mutation of the target gene in a Dox-dependent manner. Moreover, this technique can induce simultaneous conditional knockout of two target genes with 40-50% efficiency. CRISPR/Cas9-mediated cKO is also applicable in mice. This system greatly reduces the time and labor required to generate cKO ESCs, as well as mice, since it allows one-step preparation of cKO cells. Nevertheless, cells with in-frame mutations, which may behave as normal cells, cannot be eliminated due to the principles underlying this system, which relies on NHEJ-dependent mutagenesis.
REPORTER CONSTRUCT-ASSISTED CKO
DNA DSBs at the targeting site greatly enhance rates of homologous recombination (Donoho et al., 1998). Based on this mechanism, several genome editing technology-assisted methods have been developed for efficient cKO cell cloning. Flemr and Bühler introduced two homozygous loxP sites simultaneously via transfection of single-strand oligo-DNA, composed of a loxP sequence and 40 bp homology arms, TAL effector nucleases (TALENs) designed to target the site of interest, and a recombination reporter construct, which contained a 5′ puromycin-resistance gene fragment and a TALENs target sequence, followed by a full-length puromycin-resistance gene without a start codon ( Figure 1C) (Flemr and Bühler 2015). If homologous recombination mechanisms are active in the transfected cells, TALENs-induced DSB of the reporter construct results in generation of an intact puromycinresistance gene via homologous recombination. Using this method, these researchers successfully generated cKO ESCs by targeting two loxP oligo-DNA molecules on both alleles in a single step; however, this approach still requires extensive screening to obtain correct clones, due to the low efficiency (approximately 4%) of targeting of all four sites. Use of CRISPR/Cas9 instead of TALENs may improve the efficiency.
CKO VIA INVERTIBLE GENE-TRAP CASSETTE
Andersson-Rolf et al. used the Cre-regulated invertible gene-trap cassette (FLIP cassette), which relates to the gene trap tool originally developed by Melchner's laboratory for preparing cKO cells (Schnütgen et al., 2005). The FLIP cassette contains a puromycin expression unit, flanked by loxP1 and lox5171 sites, in the middle of an artificial intron sequence ( Figure 1D) (Andersson-Rolf et al., 2017). To produce cKO cells, the FLIP cassette is inserted into a coding exon of a target gene via homologous recombination, with the assistance of CRISPR/ Cas9 designed for the target site. The resulting targeted clones can be cKO cells, as CRISPR/Cas9 both assists in targeting the FLIP cassette and destroys untargeted allele(s) of the target gene via NHEJ-dependent mutagenesis. Transient expression of Cre in the targeted clone induces inversion of the FLIP cassette and knocks out the target gene by switching the splicing donor/ acceptor structure of the artificial intron. The authors produced Ctnnb1 cKO ESC clones using this method, and verified the loss of ESC dome-like morphology on introduction of Cre. The CRISPR/Cas9 vector designed in the coding exon introduces the FLIP cassette in one allele, while it could also disrupt the other allele of the gene. This smart system is applicable in both ESCs and aneuploid cells, as homologous recombination of the FLIP cassette in one allele is sufficient to generate cKO cells. Nevertheless, the system still requires relatively extensive screening, since the efficiency is around 6% (4 FLIP/-clones out of 64 isolated clones in the case of ESC screening for Ctnnb1 cKO cells). Further, gene expression from the targeted allele appears to be compromised, probably due to the selection marker unit inserted in the artificial intron of the FLIP cassette.
CKO VIA CONDITIONAL PROTEIN DEGRADATION
Conditional induction of target protein degradation is another method for generating cKO cells ( Figure 1E). Several techniques for conditional depletion of target proteins have been developed using mutant FKBP, Halo-tag, and auxin-inducible degron (AID) as tagsequences, and the small chemical compounds, Shld1, HyT13, and auxin [indole-3-acetic acid (IAA)], as regulators of degradation (Banaszynski et al., 2006;Nishimura et al., 2009;Neklesa et al., 2011). Among these approaches, the AID system is the most wellvalidated, and uses an Oryza sativa-derived TIR1 protein, which forms an E3 ubiquitin ligase complex that can induce regulated and rapid degradation of proteins fused with a 7 kDa degron tag derived from Arabidopsis thaliana IAA17, in a manner dependent on the small chemical compound, auxin. Thus, introduction of an AID-tag into a target gene in TIR1-expressing cells enables cKO of the target gene.
A recent report described one-step generation of degron-based cKO cells using an improved AID system, which employs mutated TIR1 and an auxin-derivative, 5-Adamantyl-IAA (5-Ad-IAA), to enhance sensitivity (Nishimura et al., 2020). cKO cells are prepared by disrupting the target gene with CRISPR/ Cas9 and inserting a vector encoding the mutated TIR1 and AIDtagged target gene cDNA, connected with an internal ribosome entry sequence (IRES), into the DSB site. The targeting efficiency was approximately 75% when this system was used for conditionally knocking out a single allele gene CENP-H, which locates on the Z chromosome in DT40 cells. This system is superior to the conditional genetics in terms of reversibility and fast kinetics. Therefore it is suitable for analysis of genes that require rapid depletion, such as cell cycle-related genes. A drawback of this approach is that expression of the target gene is controlled by the IRES sequence; thus target gene expression in the cKO cells does not reflect endogenous gene expression. This is also applicable to the genes in which regulatory elements in introns are eliminated. Another concern is that depletion of the target protein could be incomplete, due to the principles underpinning the system (Ng et al., 2019).
THE ALL-IN-ONE CKO METHOD
The recent study reported a novel cKO method, the all-in-one cKO method, which allows one-step and highly efficient cKO and simultaneous target gene modifications, including epitope tagging and reporter gene knockout/in, via CRISPR/Cas9-assisted homologous recombination of the all-in-one cassette in a coding exon of the target gene ( Figure 2A) (Suzuki et al., 2021). The all-in-one cassette encodes an FRT-flanked promoter-less EGFP gene, followed by a P2A peptide sequence, a FLAG-tag sequence, and the coding sequence of the target gene, upstream of the CRISPR/Cas9 target site. Since the EGFP cassette does not contain a promoter, sorting of EGFP-positive cells enables efficient isolation of cKO mESC clones at a frequency of up to 80%. Moreover, targeting of the all-in-one cassette in the presence of the DNA-PK inhibitor, M3814, which enhances homologous recombination, followed by EGFP sorting, resulted in almost 100% cKO efficiency, even in the recombination-non-proficient human fibrosarcoma cell line, HT1080 (Riesenberg et al., 2019). Given this high efficiency, homozygous targeted cKO clones could be easily isolated, even from HT1080 cells. Target gene expression can be monitored via EGFP expression in cKO cells, and protein expression can be detected using an anti-FLAG antibody; this feature greatly improves the detection sensitivity of target proteins by western blotting or immunocytochemistry, and is useful for conducting chromatin immunoprecipitation (ChIP) and crosslinking immunoprecipitation (CLIP) assays, as well as for affinity purification of binding proteins for mass spectrometric analysis.
In addition, to enable instant and strictly regulated induction of KO cells from cKO cells, a TetFE ESC line was established. TetFE ESCs have an rtTA expression cassette and a tetracycline response element-regulated FLPERT2 expression cassette in the Gt (ROSA) 26Sor locus to maintain stable expression of transgenes. A simultaneous or sequential integration of multiple gene loading vectors (SIM) system and modified SIM system were employed to introduce those genes ( Figure 2B). The SIM system was originally developed for efficient sequential introduction of unlimited number of gene loading vectors (GLVs) or simultaneous introduction of multiple GLVs into human/mouse artificial chromosomes (HAC/ MAC) (Suzuki et al., 2014;Uno et al., 2018;Suzuki et al., 2020). Both the SIM system and the modified SIM system uses gene-loading modules called SIM cassettes, which contain recognition sequences for Bxb1 and/or φC31 recombinases/integrases, to combine a maximum of three GLVs. While the SIM system utilizes the Cre/ loxP reaction for integration of the combined GLVs to the geneloading site of HAC/MAC, the modified SIM system employs CRISPR/Cas9 for integration to a safe harbor locus via NHEJdependent knock-in ( Figure 2B). Co-transfection of the GLVs and recombinases/integrases expression vectors to 3 × 10 5 target cells was sufficient for obtaining correctly recombined cell clones (Suzuki et al., 2014). It is important to know that human and mouse genomes contain pseudo-attP sequences, which are recognized by φC31 integrase (Thyagarajan et al., 2001). Therefore, validation of GLV integration to an intended site is essential for utilizing the modified SIM system. TetFE ESCs stably express rtTA and conditionally express FLP with an ERT2 domain (FLPERT2), which enables 4-hydroxytamoxifen (4-OHT)-dependent nuclear localization in a Dox-dependent manner. Therefore, KO cells can be easily induced via addition of Dox and 4-OHT. This dual regulation system completely prevents spontaneous KO induction caused by leaky activity of FLPERT2 and background expression of Dox-regulated genes. This drug-inducible feature is also advantageous for large-scale preparation of KO cells.
Application of the all-in-one cKO system in conjunction with the TetFE ESCs has been demonstrated in functional analysis of FIGURE 2 | The simultaneous or sequential integration of multiple genes (SIM) system and all-in-one conditional knockout (cKO) methods. (A) All-in-one cKO method. Green circle, nucleotides used to induce a frame-shift mutation; empty triangle, FRT site; FL, 3 × FLAG-tag sequence. (B) Schematic representation of the SIM system and the modified SIM system. The SIM system and the modified SIM system enable simultaneous loading of multiple gene loading vectors (GLVs) into a human artificial chromosome/mouse artificial chromosome vector and a safe harbor locus, respectively. The procedure to generate TetFE ESCs is shown as an example for loading multiple GLVs via the modified SIM system. Frontiers in Cell and Developmental Biology | www.frontiersin.org March 2022 | Volume 10 | Article 870629 5 the RNA helicase, DDX1, in ESCs. DEAD box RNA-helicases contain characteristic Asp-Glu-Ala-Asp (DEAD) box motifs that are involved in various RNA metabolism processes, including translation, pre-tRNA splicing, and ribosomal biogenesis (Linder and Jankowsky 2011). DDX1 is a DEAD box RNA helicase suggested to be involved in viral replication, tRNA synthesis, and miRNA processing (Fang et al., 2004;Han et al., 2014;Popow et al., 2014). Further, loss of Ddx1 stalls mouse development at the 2 to 4 cell stage, possibly due to mis-regulation of DDX1-bound mRNA, which is crucial for 1 to 4 cell stage embryo development (Hildebrandt et al., 2019); however, the precise molecular mechanisms underlying these functions have not been fully elucidated. To clarify these molecular functions, we prepared Ddx1 cKO TetFE ESCs and found that loss of Ddx1 resulted in a severe growth defect. Furthermore, the number of TUNELpositive apoptotic cells was significantly increased in Ddx1 −/− ESCs. Accordingly, expression of p53, the master-regulator of cell growth and survival, was upregulated in Ddx1 −/− ESCs. These results indicated that loss of Ddx1 activated the p53-signaling pathway. Further analysis revealed that loss of DDX1 led to an rRNA processing defect, resulting in p53 activation via a ribosome stress pathway. Consistent with these findings, the apoptotic phenotype of Ddx1 −/− ESCs was rescued by disruption of the p53 gene. These molecular analyses illustrate the practical utility of the all-in-one cKO method, while most recently developed cKO methods have only been used for proofof-principle experiments. The disadvantage of the all-in-one cKO method is that it is only applicable for genes whose promoters can drive detectable levels of EGFP expression. Further improvements will be essential to allow application of the method for genes with low expression levels.
DISCUSSION
The recent development of new strategies has greatly reduced the time and labor required for preparation of cKO cells. To encourage wider use of these cKO methods in the academic community, further improvements may be needed. While methods developed to date allow generation of cKO cells in a single step, most still require relatively large-scale screening to isolate a clone due to low cKO efficiencies of approximately 5%. Moreover, some CRISPR/Cas9-assisted methods rely on disruption of untargeted alleles ( Figures 1D,E), which could restrict the utility of the cKO cells, since cKO cells obtained by this method express lower levels of the target gene than the parental cells, as the target gene is only expressed from the targeted allele. To overcome these limitations, improvements in targeting rate are required for efficient preparation of homozygous targeted cKO clones. Application of homologous recombination-enhancing drugs/genes may improve efficiency, as demonstrated in the all-in-one cKO method. Further, production of homozygous targeted cKO clones in aneuploid cell lines should further broaden the utility of these approaches. The procedure for KO induction of cKO cells is also a potential hurdle to general application of these methods. Since stable expression of recombinases is potentially toxic to cells, transient recombinase expression is appropriate for KO induction. Drug-inducible recombinase expression systems would also be convenient, and are used in several methods. The Dox-inducible, 4-OHT-regulated system applied in the all-in-one cKO method may be optimal for strict regulation of KO induction, as it avoids background induction of KO cells, due to leaky expression/activity of KO inducers.
Conditional knockout of multiple genes can be useful for analysis of signaling pathways or functions of redundant genes. Although simultaneous cKO of two genes was demonstrated using the inducible Cas9-mediated cKO system, the double KO efficiency was 40-50%, which is insufficient to allow molecular function analysis in most cases. Moreover, the system cannot induce KO of each gene separately. Production of cKO cell lines by applying multiple-recombinases and their recognition sequences via the efficient methods reviewed here could resolve these issues.
AUTHOR CONTRIBUTIONS
TS and TH designed the study and wrote the manuscript. ST assisted the construction of figures.
FUNDING
This work was supported in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI (grant numbers JP18K06047 (TS) and JP23390256 (TH)) and by Core Research for Evolutionary Science and Technology (CREST) program of the Japanese Science and Technology Agency (JST) (JPMJCR18S4 to TS). |
A workflow to design new directed domestication programs to move forward current and future insect production
doi: 10.1093/af/vfab014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © Lecocq, Toomey Feature Article A workflow to design new directed domestication programs to move forward current and future insect production
Introduction
Domestication has irrevocably shaped the history, demography, and evolution of humans. It is a complex phenomenon which can be seen as a continuum of relationships between humans and nonhuman organisms, ranging from commensalism or mutualism to low-level management (e.g., game keeping or herd management) or, even, direct control by humans over resource supply and reproduction (Terrell et al., 2003;Smith, 2011;Teletchea and Fontaine, 2014;Zeder, 2014Zeder, , 2015. This continuum should not be seen as an obligatory succession of different relationships, which ultimately always ends by human control over reproduction, for all species involved in a domestication process. For instance, most fish domestications do not involve initial commensal relationships (Teletchea and Fontaine, 2014), and African donkeyowners do little to manage reproduction of African wild asses (Marshall et al., 2014). Moreover, it is worth noting that the domestication process 1) does not involve all populations of a particular species (e.g., some fish populations underwent domestication for aquaculture while wild conspecific populations still occur, Teletchea and Fontaine, 2014) and 2) is not irreversible (i.e., feral populations).
The complexity of the domestication process is mirrored by the diversity of past domestication histories. For instance, three main patterns of domestication histories can be identified for animal species: the "domestication pathways" (Zeder, 2012a(Zeder, , 2012b(Zeder, , 2015Larson and Fuller, 2014;Frantz et al., 2016). The commensal pathway (e.g., dog and cat domestications) does not involve intentional action from humans but, as people manipulate their environment, some wild species are attracted to parts of the human niche, and commensal relationships with humans can subsequently arise for the tamest individuals of these wild species (Zeder, 2012b;Larson and Burger, 2013). Over generations, relationships with humans can shift from synanthropic interactions to captivity and human-controlled breeding (Larson and Fuller, 2014). The prey pathway (e.g., domestications of large herbivorous mammals) requires human actions driven by the intention to increase food resources for humans. The pathway starts when humans modify their hunting strategies into game management to increase prey availability, perhaps as a response to localized pressure on the supply of prey. Over time and with the tamest individuals, these game management evolve in herd management based on a control over movements, feeding, and reproduction of animals (Zeder, 2012a;Larson and Burger, 2013). At last, the directed pathway (e.g., domestication of transport animals, Larson and Fuller, 2014) is triggered with a deliberate and directed process initiated by humans in order to control movement, food supply, and reproduction of a wild species in captive or ranching conditions (Zeder, 2012a). All pathways lead to animal population evolution shaped by new specific selective pressures of the domestication environment (Wilkins et al., 2014). The divergence from wild ancestors further increases for species for which humans reinforce their control over population life cycle while they decrease gene flow between populations engaged in the domestication process and their wild counterparts (Teletchea and Fontaine, 2014;Lecocq, 2019). This control can ultimately result in selective breeding programs or organism engineering (e.g., genetically modified organisms) that are developed to Implications • Insect farming is expected to expand in the near future, but domestication is a long and difficult process which is often unsuccessful. Considering hits and misses from past directed domestications of insects and other species, we here provide a workflow to avoid common pitfalls in directed domestication programs. • This workflow underlines that it is crucial to find relevant candidate species for domestication. Candidate species must address human need/ demand and meet a set of minimal requirements that shape their domestication potential. The domestication potential can be defined through an integrative assessment of key traits involved in biological functions. • Geographic differentiation of key traits in a candidate species and the maintenance of adaptative potential of farmed populations should also be considered to facilitate domestication and answer to future challenges.
intentionally modify some traits of interest (Teletchea and Fontaine, 2014;Lecocq, 2019). Around 13,000 years ago, a first wave of domestication happened. It concerned mainly terrestrial vertebrate and plant species that are those dominating the agricultural world today (Diamond, 2002;Duarte et al., 2007). Noteworthy examples of insects involved in this wave include the silkworm (Bombyx mori, Lepidoptera) and the honeybee (Apis mellifera, Hymenoptera) (see domestication histories reviewed in Lecocq, 2019). Many insect domestication events started recently, in the 20th century (Lecocq, 2019), concomitantly with aquatic species Hedgecock, 2012) and some crop taxa (Leakey and Asaah, 2013), during the so-called new wave of domestication (i.e., refers to the large number of domestication trials since the start of the 20th century). Most domestications of this new wave follow a directed pathway through planned domestication programs Teletchea and Fontaine, 2014;Lecocq, 2019). This new wave has been facilitated by technological advances in captive environment control and animal food production. However, the triggering factor of this wave has been the emergence of new unmet human needs. Indeed, new domestication events appear unlikely when the human needs that could be met by targeted species (e.g., human food supply) are already addressed by wild or already domesticated species (Diamond, 2002;Bleed and Matsui, 2010;Freeman et al., 2015). For instance, many of the recent aquatic species domestications have been triggered by the need to meet the rising human demand for aquatic products while wild fishery catches are no longer sufficient . Similarly, bombiculture (i.e., production of bumblebees, Hymenoptera, Bombus spp.) is an insect example of domestication triggered by an unmet human demand: the development of fruit production (e.g., tomatoes, raspberry) in greenhouses, which required importing insects such as bees to ensure the pollination ecosystem service. However, previously domesticated species, such as honeybees, are quite inefficient pollinators for such crops whereas bumblebees are ideal pollinators for these plants (Velthuis and van Doorn, 2006). This led to domestication of several bumblebee species since the 1980s (Velthuis and van Doorn, 2006). Overall, for insects, as for many other species, recent domestication programs have been triggered by needs to produce biological control agents (e.g., ladybugs, Coleoptera, Coccinellidae), pets (e.g., hissing cockroach, Blattodea, Gromphadorhina portentosa), and laboratory organisms (e.g., fruit flies, Diptera, Drosophila spp.), or for sterile insect technique development, and raw material/food production (reviewed in Lecocq, 2019).
New instances of insect domestication can be expected in the near future as several authors and international organizations claim that larger, optimized, and new insect productions will be a part of the solution to ensure human food/sanitary security and to address new demands for pets in the next decades (van Huis et al., 2013;Gilles et al., 2014;Lees et al., 2015;Mishra and Omkar, 2017;Thurman et al., 2017;Saeidi and Vatandoost, 2018). Here, we speculate that these future domestications will mainly follow a directed pathway as observed for other species involved in the new wave of domestication. These future domestication programs will be challenging since, despite technological developments, directed domestication is still a long and difficult process which often ends up being unsuccessful. Even when the life cycle is controlled by humans, major bottlenecks can still hamper the development of largescale production. Although limited amount of information about domestication failure rate is available in literature, past domestication programs of species involved in the new wave of domestication show that many new domestication programs often lasted a couple of years before being abandoned (e.g., for fish: Metian et al., 2019; for insect: Velthuis and van Doorn, 2006). The main causes of these failures are technical limitations, socioeconomic constraints, or intrinsic species features (Liao and Huang, 2000;Diamond, 2002;Driscoll et al., 2009). Potential solutions to facilitate domestication have been investigated for plants and vertebrates (e.g., Diamond, 2002;DeHaan et al., 2016;Toomey et al., 2020a). Conversely, insects have received very little attention to date (Lecocq, 2019).
Here, we consider feedbacks from past directed domestication programs of insects and other species to provide a conceptual workflow ( Figure 1) to facilitate future insect domestication programs following a directed pathway (from this point, domestication will refer in the text to the directed pathway). This workflow ranges from the selection in the wild biodiversity of biological units (at species and intraspecific levels) to start new production to the development of selective breeding programs. We considered that technical limitations are not a major issue in insect domestication. Indeed, production systems (i.e., human-controlled environments in which animals are reared and bred) are already available for several phylogenetically distant insect species with different ecology, physiology, and behavior (Leppla, 2008). Thus, future insect domestications could likely be based, with potentially minor adjustments, on already existing production systems. Therefore, we here focus on how avoiding pitfalls due to socioeconomic constraints or intrinsic species features to move forward ongoing and future directed insect domestication programs to response to human demands.
Backing the Right Horse by Finding the Right Candidate Species for Domestication
Domestication processes which meet needs that can be more easily addressed by other means (e.g., wild catches or other domesticated species), as well as productions with a low productivity and/or profitability, are often doomed to failure (e.g., Diamond, 2002;DeHaan et al., 2016). Therefore, any new planned domestication program should consider how it could respond to an unmet human requirement with a viable and efficient business model. This can be at least partially answered by an evaluation of potential candidate species for domestication before starting large-scale production.
First: identifying an unmet human need or demand to define new candidate species
Human need or demand can focus on a species of interest (species-targeted domestication). Such domestications happen 1) when a wild species already exploited by humans becomes rare (e.g., for insects see Lecocq, 2019) or protected (e.g., the European sturgeon, Actinopterygii, Acipenser sturio) in the wild, 2) to allow reintroduction for wildlife conservation (e.g., for butterflies, Crone et al., 2007), or 3) to develop sterile insect techniques (see Lecocq, 2019). At this stage, the species of interest is regarded as a candidate species that must be further studied to assess the feasibility of its domestication (Figure 1).
The need or demand for a particular ecosystem service can also spark new species farming (service-targeted domestication, see also DeHaan et al., 2016), as exemplified by bumblebee domestication (Velthuis and van Doorn, 2006). Since most ecosystem services can be ensured by numerous taxa, several candidates for domestication could be identified. This raises the need to highlight among available candidates those that maximize the chance of success to go successfully through the domestication process (DeHaan et al., 2016).
Second: the importance of an integrative assessment of candidate species
Before going any further in the domestication program development, special attention should be paid to international and national regulations regarding sampling, transport, and use of candidate species. Indeed, such regulations can prevent producing or trading a species in some areas (e.g., Perrings et al., 2010;Figure 1. A seven-step workflow to develop a fruitful insect production. 1. Identification of an unmet human demand. 2. Identifying candidate species that could meet the demand through a multifunction and multitrait assessment jointly developed with stakeholders. 3. Decision-making rules established with stakeholders highlight species with high domestication potential (here, one species but several species can be chosen). 4. Investigating the interest of geographic differentiation between wild populations (prospective units) of the species, similar to steps 2 and 3 to highlight units with high domestication potential (two units in this fictive example). 5. Creating the initial stock through pure or cross breeding strategy with attention paid to the genetic diversity of this stock (here, a cross breeding strategy is used). 6. Initial stock improvement through selective breeding programs and/or wild introgression to minimize adverse effects and reinforce beneficial domestication effects. 7. Production evolution according to human demand and environmental changes thanks to its adaptive potential and methods developed in the previous step. When no adaptation can be developed, new domestication could be considered. Wild biodiversity is considered at the species and intraspecific levels. Samways, 2018), making its domestication economically poorly attractive or pragmatically useless. They can thus limit the number of potential candidates or make a species-targeted domestication unfeasible.
Wild insect species are not all suitable candidates for domestication. Indeed, each species has a specific "domestication potential" (adapted from Toomey et al., 2020a): a quantification of how much expression of key traits is favorable for domestication and subsequent production. Several behavioral, morphological, phenological, and physiological key trait expressions have been highlighted as relevant to facilitate domestication and subsequent production (e.g., for noninsects, Diamond, 2002;Driscoll et al., 2009). By considering insect specificities, we state that these expressions include high growth rate, high food conversion ratio, generalist herbivorous feeder or omnivorous, high survival rate, short birth spacing, polygamous or promiscuous mating, large environmental tolerance, high disease resistance, gregarious lifestyle, and diet easily supplied by humans. This list should be completed with additional key traits specific to the domestication purpose. For instance, pollination efficiency is relevant for pollination-targeted domestication while nutritional quality is important for edible insect domestication. Moreover, expression of socioeconomical key traits must also be considered for domestication potential assessment such as high yield per unit, high sale value, established appeal for consumers, and useful byproducts (e.g., for silkworm; Lecocq, 2019). At last, potential environmental consequences of future production, such as risks of biological invasions associated to the development of international trade (Lecocq et al., 2016), should be considered through the evaluation of relevant traits (e.g., invasive potential, which corresponds to the ability of a species to trigger a biological invasion out of its natural range). Overall, the set of key traits can be defined thanks to advice or expectations of stakeholders (consumers, environmental managers, policy makers, producers, and socioeconomists) (Figure 1; see similar approach for fish in Toomey et al., 2020a).
It is worth noting that key traits 1) are involved in different biological functions (behavior, growth/development, homeostasis, nutrition, reproduction) and 2) are not necessarily correlated among each other, implying that expression of a trait cannot be inferred from other traits (Toomey et al., 2020b). This means that species domestication potential must be assessed by a multifunction and multitrait integrative framework (Figure 1). Moreover, species might present specificities in the wild but those might not be maintained in production systems because expression of key traits, as any phenotypic trait, is determined by genetic divergence and environment, as well as the interaction between these two factors (Falconer and Mackay, 1996). Therefore, an efficient assessment should be performed in experimental conditions as close as possible to the production system. Overall, such an assessment can be seen as heavy-going and time-and money-consuming. However, the complexity of multifunction and multitrait assessment in standardized conditions is offset by the minimization of the risk to start a long and difficult domestication program with the wrong candidate species.
Third: reaching a consensus to choose relevant candidate(s) to start domestication
Making an integrative assessment of domestication potential should not hide the fact that some key traits can be more important than others. For instance, very low survival rate or low reproduction rate during the assessment will certainly stop ongoing domestication trials because they prevent the completion of the life cycle. Therefore, minimal expression threshold (i.e., minimum threshold for a trait expression which must be met or else the biological unit is not suitable for domestication programs; e.g., a survival rate below which an animal production would not be economically feasible) should be defined, potentially by a panel of stakeholders, for the most important traits relatively to the domestication purpose (see similar approaches in DeHaan et al., 2016;Toomey et al., 2020a). When a species does not meet this threshold, it must be regarded to be void of domestication potential. This threshold must be carefully defined, even in species-targeted domestication programs, to avoid starting large-scale domestication programs with issues that could be costly and slow or impossible to fix later in the process.
When comparing key trait expressions between species, it is likely that a candidate displays a favorable expression for a specific key trait (e.g., best nutritional value) but not for another trait (e.g., lowest survival rate). This requires making a consensus between results of key trait assessment to identify the best candidate species for a service-targeted domestication or to objectively assess the relevance of a species-targeted domestication (Figure 1, e.g., for noninsect species, Quéméner et al., 2002;Alvarez-Lajonchère and Ibarra-Castro, 2013;DeHaan et al., 2016). Scoring solutions could be used, considering weighting coefficients to integrate the potential differential levels of importance of key traits due to socioeconomic factors, absolute prerequisites for domestication, or production constraints. Weighting coefficients can be defined through surveys of stakeholders' expectations ( Figure 1; see examples in Quéméner et al., 2002;Toomey et al., 2020a). Since expectations might vary across stakeholders, decision making should be based on a consensus between all parties involved (see strategies to solve complex scientific and socioeconomic issues and consensus solutions in Hartnett, 2011;Wyborn et al., 2019;Toomey et al., 2020a). Ultimately, weighted integrative assessment of candidate species allows highlighting those that would likely foster new fruitful domestication programs for servicetargeted domestication or confirm/infirm the relevance of a species-targeted domestication process. These candidates are thus called species with high domestication potential.
Getting Off on the Right Foot Thanks to Intraspecific Diversity
Fourth: having the best intraspecific unit to start new domestication programs Once a new species with high domestication potential has been identified, considering geographic differentiation between allopatric groups of conspecific populations (commonly observed in insects; e.g., Araki et al., 2009;Uzunov et al., 2014) can be helpful to further facilitate domestication programs (Toomey et al., 2020a). Indeed, such population groups can present divergent demographic histories, which can shape genetic and phenotypic specificities through 1) gene flow limitation or disruption, 2) random genetic drift, and/or 3) local adaptation (Mayr, 1963;Avise, 2000;Hewitt, 2001;Toomey et al., 2020a). This could ultimately lead to differentiation in key traits and, thus, to divergent domestication potentials between wild population groups. A few past domestication histories show that geographic differentiation can facilitate domestication (e.g., for fishes: Toomey et al., 2020a;for crops: Leakey, 2012;. In insects, the domestication of the buff-tailed bumblebee (Hymenoptera, Bombus terrestris) is one of the few stunning examples where populationspecificity inclusion in domestication programs fostered a fruitful economic development. The buff-tailed bumblebee displays significant differentiation in key traits (e.g., foraging efficiency, colony size, and diapause condition) between differentiated groups of populations corresponding to subspecies (Velthuis and van Doorn, 2006;Kwon, 2008;Lecocq et al., 2016). In the early years of production, European bumblebee breeders tried to domesticate several subspecies. Within a short space of time, one subspecies (B. terrestris dalmatinus) proved to have superior characteristics from a commercial point of view (i.e., largest colonies, efficient highest rearing success rate, high pollination efficiency) and became the dominant taxa in the bombiculture industry (Velthuis and van Doorn, 2006). Similarly, non-African honeybees were favored for domestication and production due to facilitating key traits (e.g., low tendency to swarm, survival in temperate areas, low aggressiveness) for beekeeping over African honeybees (Wallberg et al., 2014).
Potential importance of geographic differentiation for insect domestication programs raises the question about how it should be integrated in domestication processes. To this end, a new integrative approach has been recently developed for fish domestication (see Toomey et al., 2020a). This approach provides an integrative assessment of differentiated allopatric population groups through three steps (Figure 1). The first step aims at classifying wild populations of a targeted species in prospective units through phylogeographic or systematic methods. These units are groups of allopatric populations that are likely differentiated in key trait expressions. The second step provides an integrative multifunction and multitrait assessment, similar to interspecific comparison of domestication potential but applied to prospective units. Finally, the last step highlights prospective units with higher domestication potentials (so-called units with high domestication potential, UHDP) through the calculation of a domestication potential score through the help/advice from stakeholders (see Toomey et al., 2020a).
Fifth: constituting the best stock to start new domestication programs
When several UHDP are highlighted as of interest, the question can be raised regarding which strategy should be adopted to constitute the initial stock ( Figure 1): 1) keeping only one UHDP or breeding several UHDP apart ("pure breeding" strategy) or 2) mixing UHDP ("cross breeding" strategy) (Falconer and Mackay, 1996). Pure breeding consists of starting with one biological unit and continuously improving it through time (e.g., for B. terrestris, Velthuis andvan Doorn, 2006 or A. mellifera, Uzunov et al., 2014). It is an effective strategy when one biological unit presents a much higher domestication potential than others. In contrast, crossbreeding could be an interesting alternative (e.g., see trials with tasar silkworm, Lepidoptera, Antheraea mylitta, Lokesh et al., 2015) when several units present a similar domestication potential or complementary interests. It consists of crossing two or more biological units aiming at having progeny with better performances than parents through complementary of strengths of the two parent biological units and heterosis (i.e., hybrid vigor). However, it is a hit-or-miss strategy since results are hardly predictable (e.g., negative behavioral consequences in A. mellifera crossings, Uzunov et al., 2014). The choice regarding which strategy should be used must made on a case-by-case basis.
Further attention should be paid to genetic diversity when constituting the initial stock ( Figure 1). If this stock is constituted with a low number and/or closely related individuals, the resulting low global genetic diversity of farmed populations will quickly lead to inbreeding issues, which can be especially damaging in some insect groups such as Hymenoptera (Gerloff and Schmid-Hempel, 2005). It is even more important in the pure breeding strategy which most likely leads to a lower initial genetic diversity than cross breeding approaches. Therefore, care should be taken that a sufficient number of individuals/families (i.e., sufficient effective size) is considered (i.e., sampling strategy) to 1) have a sufficient initial genetic variability and avoid to sample kin individuals which increase risks of future inbreeding issues, 2) mitigate the risk of sampling suboptimal genotypes which are not representative of the population group, and 3) have a sufficient genetic variability for future selective breeding programs (Toomey et al., 2020a).
Going Further in the Domestication Process:
The Wise Way
Sixth: improving stocks undergoing domestication
During domestication, farmed populations undergo new selective pressures from the rearing environment, a relaxation of wild environmental pressures, and other genetic processes, such as founder effect, genetic drift, or inbreeding (Wilkins et al., 2014). These processes lead to genetic, genomic, and phenotypic differentiations (Mignon-Grasteau et al., 2005;Wilkins et al., 2014;Milla et al., 2021), which are overall poorly studied in insects compared with other taxa (Lecocq, 2019). Yet, they can trigger changes in key trait expressions that are often observed in domesticated species (e.g., for insects: higher tameness, lower aggressiveness toward humans and conspecifics (Latter and Mulley, 1995;Adam, 2000;Krebs et al., 2001;Zheng et al., 2009;Chauhan and Tayal, 2017;Xiang et al., 2018). These changes can facilitate domestication or lead to an improvement of performances (i.e., beneficial changes) that enhances the profitability of the production sector (e.g., higher silk production in silkworm; Lecocq, 2019). However, some changes can also be unfavorable for domestication and subsequent production (i.e., adverse changes) as shown in other taxa (e.g., reproduction issues in fish, Milla et al., 2021).
Selective breeding programs are widely used as a solution to overcome adverse changes or reinforced beneficial changes shaped by domestication (Figure 1). The efficiency of such programs was demonstrated for several taxa (e.g., broiler chicken, Gallus gallus domesticus, Galliformes, Tallentire et al., 2016, Atlantic salmon, Salmo salar, Salmoniformes, Gjedrem et al., 2012, including insects (e.g., Adam, 2000;Simões et al., 2007;Zanatta et al., 2009;Bourtzis and Hendrichs, 2014;Niño and Cameron Jasper, 2015). Despite the success of numerous breeding programs, they can also lead to negative-side effects. This is well known in livestock (Rauw et al., 1998) but it was also investigated in insects (e.g., Oxley and Oldroyd, 2010). An alternative solution to solve deleterious changes shaped by domestication relies on introgression of wild individuals in farmed populations (Figure 1, Prohens et al., 2017). For instance, in insects, a hybridization was performed between wild African and domesticated European A. mellifera populations to create an Africanized strain which would be better adapted to tropical conditions and present a higher honey production (Spivak et al., 2019). However, despite its efficiency for honey production, its defensive behavior quickly became an issue and is considered nowadays as a matter of concern in Americas ( Spivak et al., 2019). Overall, the development of selective breeding programs or wild introgression in insect domestication could be of great interest but attention should be paid to traits selected and to potential negative consequences.
Seventh: keeping one step ahead by maintaining the adaptive potential of production
The relevance of an insect production depends on the socioeconomic and environmental contexts which can change over time. First, the triggering factor of domestication events, the human demand/need, can change with time and/or additional demands can appear aside from the original ones due to market fluctuations, new regulations, or technological development. Second, ongoing global changes (e.g., global warming, pollution) can impact production systems (i.e., outdoor production) and/or availability of important resources for farming (Decourtye et al., 2019). This places a premium on maintaining the adaptive potential of insect production over time, jointly with stakeholders, through species intrinsic features, selective breeding programs, wild individual introgressions, or new domestication program developments (Figure 1).
Insect farming can face these changes thanks to species intrinsic features such as large climatic tolerance or generalist diet. In the context of global changes, the ability to cope with environmental changes is thus a valuable information that should be considered early in the process, during the assessment of candidate species domestication potential (see examples of species-specific responses to climate change or abiotic parameters between closely related species in (Oyen et al., 2016;Martinet et al., 2020).
Alternatively, insect productions can evolve to deal with socioeconomic and environmental changes through selective breeding programs (i.e., continuous adaptation) to improve farmed populations (through trait selection or wild introgression) or create new specialized strains (Decourtye et al., 2019). However, selective breeding programs often drive to a loss of genetic diversity, which can trigger a lower resilience of farmed stocks (Gering et al., 2019). Indeed, genetic variability defines a biological unit's ability to genetically adapt to future challenges and contributes to global species biodiversity, which maximizes species survival chances in the long term (Sgrò et al., 2011). This appears even more important considering that some rearing practices can quickly lead to a loss of genetic variability (e.g., beekeepers specializing in queen breeding and consequently a large amount of progeny originate from a few queen mothers, Meixner et al., 2010). Moreover, genetic variability can also be important for the population fitness (e.g., this variability is essential for disease resistance and homeostasis in A. mellifera, Meixner et al., 2010). Overall, the maintenance of genetic variability is capital ( Figure 1) and could be facilitated by wild introgressions (Prohens et al., 2017).
Finally, in extreme cases in which farmed stocks cannot face/be adapted to new socioeconomic and environmental contexts, it will be necessary to start new domestication programs using new candidates (new wild species or population groups).
Conclusion
Insect farming is expected to expand in the future but remains challenging because of the difficulty to domesticate new species. We proposed a conceptual workflow to avoid major problems commonly encountered during domestication programs. We underlined the importance of 1) considering how new species production could respond to an unmet human demand with a viable and efficient business model and 2) assessing the domestication potential of candidate species through an integrative assessment. We argued that geographic differentiation between wild populations of a candidate species can be valuable. At last, we emphasized the importance of maintaining the adaptive potential of productions to answer to current and future challenges. |
Response of the multiple-demand network during simple stimulus discriminations
The multiple-demand (MD) network is sensitive to many aspects of task difficulty, including such factors as rule complexity, memory load, attentional switching and inhibition. Many accounts link MD activity to top-down task control, raising the question of response when performance is limited by the quality of sensory input, and indeed, some prior results suggest little effect of sensory manipulations. Here we examined judgments of motion direction, manipulating difficulty by either motion coherence or salience of irrelevant dots. We manipulated each difficulty type across six levels, from very easy to very hard, and additionally manipulated whether difficulty level was blocked, and thus known in advance, or randomized. Despite the very large manipulations employed, difficulty had little effect on MD activity, especially for the coherence manipulation. Contrasting with these small or absent effects, we observed the usual increase of MD activity with increased rule complexity. We suggest that, for simple sensory discriminations, it may be impossible to compensate for reduced stimulus information by increased top-down control.
Introduction
Diverse studies examining a range of cognitive demands have found of a set of frontalparietal regions that are consistently involved in a variety of tasks, ranging from response inhibition to working memory to decision making (e.g., Duncan & Owen, 2000;Fedorenko, Duncan, & Kanwisher, 2013;Niendam et al., 2012;Stiers, Mennes, & Sunaert, 2010).
Included in this pattern are regions of the dorsolateral prefrontal cortex, extending along the inferior/middle frontal gyrus (IFG/MFG), and including a posterior-dorsal region close to the frontal eye field (pdLFC), parts of the anterior insular cortex (AI), pre-supplementary motor area and adjacent anterior cingulate cortex (pre-SMA/ACC), and intraparietal sulcus (IPS).
Activity in the MD network increases with increases in many kinds of task difficulty or demand, such as with additional subgoals (e.g., Farooqui et al., 2012), greater working memory demand (Dara et al., 1997), resisting strong competitors (e.g., Baldauf & Desimone 2014), task switching (e.g., Wager et al., 2004), or a wide range of other task demands (e.g., Crittenden & Duncan, 2014;Jovicich et al., 2001;Marois, Chun, & Gore, 2004;Woolgar, Afshar, Williams, & Rich, 2015). Increased activity in more difficult conditions can also be accompanied by stronger information coding, shown by multivoxel pattern analysis (e.g., Woolgar, Afshar, et al., 2015;Woolgar, Hampshire, Thompson, & Duncan, 2011;. Reflecting these widespread effects of demand, the MD network has been suggested to implement top-down attentional control, optimally focusing processing for the requirements of a current task (Miller & Cohen, 2001;Duncan, 2013; see also Norman & Shallice, 1980). One simple way to manipulate task difficulty is through the quality of stimulus information.
Some experiments have shown clear MD responses as stimulus discriminability decreases (e.g., Crittenden et al., 2014;Deary et al., 2004;Holcomb et al., 1998;Jiang & Kanwisher, 2003;Sunaert, Van Hecke, Marchal, & Orban, 2000;Woolgar et al., 2011), but this has not always been the case (Cusack, Mitchell, & Duncan, 2010;Dubis et al., 2016;Han & Marois, 2013;Muller-Gass & Schroger, 2007). For example, Cusack et al. (2010) contrasted hard and easy trials of a task in which participants had to detect a barely perceptible ripple in an oscillating dot field and found no neural activation differences between the two sensory difficulty levels, despite substantial differences in behavioral performance, and robust BOLD contrast to a different task manipulation (attention switching).
In an important study, Han and Marois (2013) investigated activity in parts of the MD system during a task in which three letter targets were to be identified in a rapid stream of digit nontargets. In the baseline condition, the three letters occurred in immediate succession; to increase demand, they either inserted a nontarget into the series of three targets, or reduced exposure duration. While activity in frontal-parietal areas increased with the addition of a distractor, exposure duration had little effect. To interpret their findings, Han and Marois (2013) appealed to the distinction made by Norman and Bobrow (1975), between datalimited and resource-limited behavior. Norman and Bobrow (1975) proposed that, for any task, some function (the performance-resource function or PRF) relates performance to investment of attentional resources. When this function is increasing, behavior is said to be resource-limited, and additional investment is repaid by improved performance. When the function asymptotes, further investment has no positive effect, and performance is said to be data-limited. In line with a link of MD activity to attentional investment, Han and Marois (2013) used these ideas of data-and resource-limitation to explain their findings. They proposed that, in their task, brief exposure duration created data limits, which could not be offset by increased fronto-parietal recruitment, while adding a distractor introduced resource limits by calling for increased attentional focus. In general it is not known when performance will be resource-or data-limited, but within this general framework, many patterns of results are possible. Figure 1A illustrates a case in which, as difficulty level varies, there is no reason to expect increased attentional allocation.
In this case, PRFs asymptote at different performance levels for the different levels of task difficulty, but across difficulty levels, the asymptote occurs at the same level of allocated resource. Figure 1B illustrates an opposite case, with increased task difficulty potentially offset by increased resource allocation. This uncertainty over the role of attentional investment in different cases of perceptual discrimination could help to explain disparate results in the literature, with some cases (e.g. Han and Marois (2013), manipulation of exposure duration) more resembling Figure 1A, and others (e.g. Han and Marois (2013), distractor manipulation) more resembling Figure 1B.
In our first experiment, we sought to strengthen the evidence that, for simple sensory discriminations, MD activity can be rather independent of task difficulty, providing an exception to the "multiple demand" pattern. For this purpose we used a motion discrimination task with two kinds of difficulty manipulation -motion coherence and salience of taskirrelevant dots. For the strongest possible effect, we manipulated both variables over a wide range, moving performance from close to ceiling to close to chance. In the task demand literature, several studies have shown that, as opposed to a monotonic increase of MD activity with task difficulty, there was an inverted U-shape response (Callicott et al., 1999;Linden et al., 2003), or a plateau after a certain difficulty level (Marois & Ivanoff, 2005;Todd & Marois, 2004;Mitchell & Cusack, 2008). A possible interpretation is that MD activity initially increases with task demands, but plateaus or even declines once the task becomes impossible even with maximal attention. In our study we examined MD activity over the full range of possible task difficulties.
In addition to manipulating both aspects of difficulty over a wide range, between participants we varied whether difficulty levels were mixed or blocked. In the mixed design, levels of difficulty were presented in random order, without advance cueing of the level to be experienced on a given trial. In contrast, difficulty level was known in advance in the blocked design. With this manipulation, we asked whether MD activity is driven more proactively, by expectancy of forthcoming demand, or more reactively, when high demand is experienced on a current trial.
Finally, in modelling our fMRI data, we attempted to remove effects of decision time, expected to increase with either sensory or selection difficulty. In two prior studies of motion coherence, trials were modelled simply as events, without regard for their duration (Kayser et al., 2010a(Kayser et al., , 2010b. In this case, greater brain activity associated with decreasing motion coherence may simply have reflected longer processing times. To diminish such effects, our fMRI model explicitly included decision time for each trial.
Though PRF shapes are generally unknown, our use of two different demand manipulations afforded the possibility of different outcomes. In particular, we expected that top-down control could be especially important in the irrelevant-dots condition, leading to larger effects of demand on MD activity. Though Experiment 1 showed results in line with this expectation, they occurred against a background of generally weak effects, and no significant difference between the two manipulations. In Experiment 2 we reexamined coherence and irrelevantdots conditions in a new group of participants, and compared these sensory demands with a manipulation of rule complexity.
Participants
Participants were randomly assigned to either the blocked or mixed group, with this variable manipulated between participants to minimize carryover effects. A total of 40 participants took part in the experiment. Twenty-one participants (9 male, 12 female, ages 19-31, mean = 25.7) took part in the blocked group, and nineteen participants (11 male, 9 female, ages 19-36, mean = 23.9) took part in the mixed group. Participants were recruited from the volunteer panel of the MRC Cognition and Brain Sciences Unit and paid to take part. An additional 16 participants were excluded (10 participants had excessive motion > 5mm, and another 6 had poor performance with accuracies more than three median absolute deviations below the median in at least one condition). All participants were neurologically healthy, right-handed, with normal hearing and normal or corrected-to-normal vision. Procedures were carried out in accordance with ethical approval obtained from the Cambridge Psychology Research Ethics Committee, and participants provided written, informed consent before the start of the experiment.
Experimental Setting and Design
Each participant performed two conditions of a motion coherence task, referred to here as the coherence condition and the irrelevant-dots condition. Each condition spanned six levels of difficulty. Difficulty type and level served as within-subject factors. This resulted in a group (blocked vs. mixed) × difficulty type (coherence vs. irrelevant-dots) × difficulty level (level 1 ~ level 6) design.
Stimuli and Procedures
The task structure was similar for both blocked and mixed designs (see Figure 2). On each trial, participants were presented with a random dot kinematogram (RDK) displayed for 200 ms, with an interval of 2-3 s between RDKs of successive trials. Participants were asked to judge the direction of the dominant dot motion, leftward or rightward. They were given 2 s to press one of two response buttons (up or down) to indicate their decision. The mapping between stimulus (left or right) and response (up or down) varied randomly between blocks, ensuring that, across the whole experiment, there were equal numbers of left-up/right-down and left-down/right-up trials for each difficulty level in each condition.
Trials were run in blocks of six. At the beginning of each block, the response mappings were displayed on the screen during a 2 s instruction period preceding the first trial, and remained on the screen throughout the entire block. The response mappings were indicated by two arrows above and below each other within the dot field aperture, with one arrow pointing right and the other pointing left. In the blocked version, information about the difficulty level of the following block was also shown on the screen (e.g., 'Difficulty Level is 1') during the instruction period; while in the mixed version, participants were shown the instructions 'Prepare for Next Block'. The difficulty level of the six trials in a block remained the same in the blocked design, covering all six difficulty levels every six blocks; while in the mixed design each block contained one trial of each difficulty level randomized within the block.
Participants were given two practice blocks of each condition (coherence and irrelevant-dots) before entering the scanner. Within the scanner, each condition constituted a separate run, each lasting ~18 minutes. The order of the two conditions was counterbalanced between participants. In each run there were 60 blocks in total, thus 60 trials per difficulty level, and 30 trials of each left/right motion direction in each difficulty level. Figure 2C illustrates coherence and irrelevant-dots conditions across the six difficulty levels.
In each RDK there were 64 red dots (RGB channels [112.5, 0, 0]) moving dominantly either left or right for 200 ms (circular aperture with diameter of visual angle ~8.5∘, dot size = 12 pixels diameter, dot speed = 5 pixels/s, dot lifetime = 5 frames). In the coherence condition, only red dots were present, and difficulty was manipulated by decreasing the percentage of the dots that were moving coherently. The six difficulty levels corresponded to 85%, 60%, 40%, 25%, 15%, or 10% of the dots moving either left or right, while the remaining dots moved in random directions. In the irrelevant-dots condition, the red dots were fixed at 85% coherence, but an additional distractor dot field was present. The distractor dot field consisted of 576 yellow dots, all of which moved randomly, with a net direction of zero (dot size = 12 pixels, dot speed = 7 pixels/s, dot lifetime = 5 frames). Participants were asked to ignore the yellow dots, and judge the dominant motion direction of the red dots. Six levels of difficulty were created by increasing the salience of the yellow distractors (RGB channels [21.25,21.25,0],[42.5,42.5,0], [85, 85, 0], [127.5, 127.5, 0], [191.25, 191.25, 0], and [255, 255, 0]). These values were selected from previous pilot testing.
Visual stimuli were displayed on a 1920×1080 (visual angle 25.16×14.31∘ screen with a refresh rate of 60 Hz, which the participants viewed through a mirror placed on top of the head coil. The distance between the participant and screen was approximately 1565 mm. Stimulus presentation was controlled using the Psychophysics Toolbox (Brainard, 1997) in Matlab (2014a, Mathworks, Natick, WA).
The data were preprocessed and analyzed using the automatic analysis (aa) pipelines and modules (Cusack et al., 2014), which called relevant functions from Statistical Parametric Mapping software (SPM 12, http://www.fil.ion.ucl.ac.uk/spm) implemented in Matlab (The MathWorks, Inc., Natick, MA, USA). EPI images were realigned to correct for head motion using rigid-body transformation, unwarped based on the field maps to correct for voxel displacement due to magnetic-field inhomogeneity, and slice time corrected. The T1 image was coregisted to the mean EPI, and then coregistered and normalized to the MNI template.
The normalization parameters of the T1 image were applied to all functional volumes. The functional data were high-pass filtered with a cutoff at 1/128 Hz, and spatial smoothing of 10 mm FWHM was applied.
Statistical analyses were performed first at the individual level using general linear modeling (GLM). For correct trials, separate regressors were created for each combination of condition and difficulty level. As errors can be a strong driver of MD activity (Kiehl et al., 2000;Ullsperger & Cramon, 2004), error trials and no-response trials were removed using separate regressors. A separate regressor was created for the cue period at the start of each block. All regressors were created by convolving the interval between stimulus onset and response with the canonical hemodynamic response function. mixed), difficulty type (coherence vs. irrelevant-dots), difficulty level (level 1 ~ level 6), and ROI (7 MD ROIs). We also performed the same ANOVA on the motion-sensitive visual area MT, using the ROI defined in the SPM anatomy toolbox.
An additional whole-brain voxelwise analysis was also performed, to detect any regions that showed a significant positive linear trend for difficulty level, separately for each difficulty type. Activation maps were thresholded at p < 0.05 (FDR corrected).
Experiment 2
A separate set of participants (n = 24, 18 female, ages 19-30, mean = 24.4) was recruited to perform the coherence and irrelevant-dots conditions along with an additional rule condition. 5 additional participants were excluded (1 because the top of the brain was not acquired, 2 who had head movements > 5 mm, and 2 who had outlier reaction times more than three median absolute deviations above the median). All participants performed the blocked design.
The coherence and irrelevant-dots conditions used a subset (levels 1, 3, and 5) of the same stimuli as previously described, except this time ( Figure 3A) the dots went in one of four directions (15°, 65°, 115°, 165°). The stimuli and response-mappings for the rule condition are illustrated in Figure 3. Participants responded using the index and middle finger of each hand on the four buttons of a response pad (left hand middle finger for the first button, left hand index finger for the second button, right hand index finger for the third button, and right hand middle finger for the fourth button), with a direct spatial mapping between stimulus direction and response key ( Figure 3B, level 1. The dot fields in the rule difficulty condition had high coherence (85%) and did not include yellow dots. However, rule complexity was manipulated using three different mappings between stimulus direction and response key ( Figure 3B).
At the beginning of each block, participants were presented with a cue indicating the difficulty level of the block. After processing the cue, they were able to press a button to begin a consecutive 6 trials of that condition. Each RDK was presented for 200 ms.
Participants had up to 10 s to respond, and after a button was pressed, a 2 s ISI preceded the next trial. At the cue for the next block, participants were given feedback of their performance accuracy as well as mean reaction time for the previous block.
Participants were given two practice blocks of each condition (coherence, irrelevant-dots, and rule) before entering the scanner. Within the scanner, each condition constituted a separate run. The order of the three conditions was counterbalanced across participants. In each run there were 24 blocks in total, thus 48 trials per difficulty level.
115°, 165°). Additional yellow dots (not shown) were added only in the irrelevant-dots condition. (B)
Participants were asked to use a response pad to indicate the direction of the moving dots by pressing the corresponding button. A direct mapping (level 1) was used for coherence and irrelevant-dots conditions, while all 3 rules were used in the rule difficulty condition.
Behavioral results
As shown in Figure 4A, accuracy decreased while reaction times increased with difficulty in both groups. Overall, proportion correct decreased from a mean of 93.5%, to a mean of 63.0% from the easiest to the hardest difficulty level.
The Greenhouse-Geisser correction was used to correct for non-sphericity. For accuracy, there were significant main effects of condition, F(1,38) = 4.1, p = 0.049, with slightly higher accuracy for irrelevant-dots, and difficulty level, F(5,190) = 240.36, p < 0.001. There was no main effect of group, F(1,38) = 0.3, p = 0.61, and no interactions. Analysis of reaction times showed a significant main effect of difficulty level, F(5,190) = 69.6, p < 0.001. The reaction time analysis also showed a significant but small interaction of condition × difficulty level, F(5,190) = 3.8, p < 0.01, but no other effects. Results averaged over bilateral MD regions are shown in Figure 4B, separately for each condition and group. As a first step, we used 2-way ANOVAs (group × difficulty level) to examine the effect of difficulty separately in each condition, averaged across all MD ROIs. In the coherence condition, the effect of difficulty was not close to significance, F(5,190) = 1.7, p = 0.14. For the irrelevant-dots condition, in contrast, increased activity across difficulty levels was significant, F(5,190) = 3.1, p = 0.01. There were no significant interactions with group.
fMRI results
Next we tested linear increases with difficulty level in each condition separately. Figure 4). Though absolute activation levels differed over MD ROIs, trends were largely similar across ROIs ( Figure 4B). The ANOVA showed a significant main effect of ROI, F(6,228) = 37.3, p < 0.001, along with a significant interaction of ROI and difficulty level, F(30,1140) = 2.6, p = < 0.001.
To check that our ROI analysis did not miss important effects elsewhere in the brain, we also carried out a standard whole-brain analysis, combining data for blocked and mixed groups, and testing for a linear increase across difficulty levels (see Methods). For the coherence condition, no significant voxels were found anywhere in the brain. For the irrelevant-dots condition, beyond the expected large increases in visual cortex, the test showed scattered, small regions close to our MD ROIs, including preSMA/ACC, AI, and regions of lateral frontal cortex.
Lastly, we tested for significant linear increases or decreases in individual participants (see Methods), again combining blocked and mixed groups, and using a whole-MD ROI. With 40 participants and an alpha level of .05, for each test we should expect 2 participants to be judged significant by chance. For the coherence condition, there were 10 significant increases but also 8 significant decreases. For the irrelevant-dots condition, there were 17 significant increases and 3 significant decreases. Overall, these results are broadly similar to those from standard random-effects analysis, but further, they suggest a significant degree of heterogeneity between participants.
ROI results for MT are shown in Figure 4C. In line with prior results (Rees, Friston, & Koch, 2000), MT activity generally declined with increasing difficulty of extracting the motion signal. A 3-way ANOVA with factors group (blocked vs. mixed), condition (coherence vs. irrelevant-dots), and difficulty level (level 1 -level 6) showed a significant main effect of difficulty level, F(5,190) = 11.7, p < 0.001. There was also a group by level interaction, F(5,190) = 2.9, p = 0.03, reflecting a stronger difficulty effect in the blocked group. No other significant effects were observed. Tests of within-subjects contrasts on difficulty level showed a significant negative linear trend, F(1,38) = 58.6, p < 0.001.
Behavioral results
In Experiment 2, participants performed the coherence, irrelevant-dots, and rule conditions.
Behavioral data are shown in Figure 5A. Separate condition (sensory, selection, and rule) × difficulty level (level 1 ~ level 3) ANOVAs were performed on accuracy and reaction time.
fMRI results
Results for MD regions are shown in Figure 5B. In this experiment, neither coherence nor irrelevant-dots conditions showed any trend towards increasing activity with increasing difficulty, in contrast to results from the rule condition. In the MD regions, we found significant 2-way interactions of condition and difficulty level, F(4,92) = 2.9, p < .05, and ROI and difficulty level, F(12,276) = 3.6, p < .01, as well as a 3-way interaction of condition, difficulty level, and ROI, F(24,552) = 2.2, p < .05. Further we tested for linear increases across difficulty levels in each condition separately. Difficulty level showed a significant linear trend in the rule condition, F(1,23) = 4.5, p < .05; however, there were no linear trends for either coherence, F(1,23) = 1.1, p = 0.32 or irrelevant -dots F(1,23) = 0.1, p = 0.76.
Whole-brain analysis showed no voxels with a significant linear increase across difficulty levels, either for coherence or irrelevant-dots conditions. For the rule condition, significant effects were found in lateral parietal and lateral frontal cortex bilaterally. Tests on individual participants showed 9/24 increases and 6/24 decreases in the coherence condition; the same in the irrelevant-dots condition; and in the rule condition, 14/24 increases and 2/24 decreases.
Discussion
The characteristic of fronto-parietal "multiple-demand" regions is increased activity for many different kinds of task difficulty. Here, we pursued mixed previous findings suggesting a partial exception -in some cases, MD activity seems largely insensitive to the difficulty of sensory discriminations. To obtain the strongest possible test of such insensitivity, using a motion coherence task, we manipulated two aspects of sensory difficulty over the widest possible range, from very easy to close to chance. We also compared results with difficulty fixed or variable across a block of trials. To ensure good power, across two experiments we tested a total of 64 participants.
Clear results were obtained for a manipulation of motion coherence. Across experiments and mixed or blocked variations of difficulty level, there was no hint of consistently increased MD activity as performance changed from close-to-ceiling to close-to-chance. Following Han and Marois (2013), these results can be interpreted in terms of the distinction drawn by Norman and Bobrow (1975) between data and resource limitations. For motion coherence, the results suggest a scenario similar to that depicted in Figure 1A: decreasing coherence simply decreases the quality of sensory data, and this cannot be offset by increased attentional focus or top-down control.
An intriguing result was revealed by examining participants individually. Even for motion coherence, there was a clear suggestion of some participants showing a linear increase of MD activity across difficulty levels. These participants were matched, however, by similar numbers showing decreases. It is worth noting that, under the framework of Norman and Bobrow (1975), altered resource allocation is an option whether or not performance is actually resource-limited. When resource allocation has little effect on performance, it may vary idiosyncratically between participants.
Results were less clear for the salience of irrelevant dots. Following Han and Marois (2013), we expected that MD activity might increase with the salience of irrelevant dots, reflecting stronger attempts to focus only on the relevant red dots. Results of Experiment 1 were somewhat in line with this prediction, though even with 40 participants, the effect was not sufficiently strong to differ significantly from the null effect for coherence. In Experiment 2, even irrelevant-dots showed no hint of an overall difficulty effect. Across experiments, results for individual participants again showed a mixture of increases and decreases. Though such variable results lead to no strong interpretation, a reasonable speculation concerns variable strategies. In one extreme case, the participant could make no attempt to separate red and yellow dots, in which case yellow dots simply decrease motion coherence, and results should resemble those of a direct coherence manipulation. Under our presentation conditions, effective top-down separation of the two dot fields may have been hard or impossible to achieve, making unselective processing the dominant strategy. In some cases, however, increasing the salience of yellow dots could have increased top-down attempts to ignore them, reflected in increased MD activity. Across many different kinds of cognitive demand, it seems that scenarios like that of Figure 1B are by far the most common. In most cases -including the rule complexity case we used in Experiment 2 -increased cognitive demand calls for increased top-down input, ensuring optimal focus on task-relevant processing. The results show, however, that this is not a universal rule. In line with the ideas of Norman and Bobrow (1975), increased attentional focus may be ineffective in overcoming simple limitations of sensory data.
As reviewed in the Introduction, the literature contains mixed findings concerning the MD response to reduced stimulus discriminability. In speeded tasks, for example, strong increases in MD activity have been reported as stimuli to be discriminated are made more similar (Jiang & Kanwisher, 2003;Woolgar et al., 2011). As we have indicated, in general we do not know the shapes of PRFs for different tasks. Rapidly deciding which of four lines is shortest, for example, may have very different attentional requirements from a global judgment of motion direction as used in the present work.
While many studies in the literature show increasing MD activity with increasing task demands, there have also been studies that have showed decreased MD activity (Bor et al., 2003), an inverted U-shape response (Callicott et al., 1999;Linden et al., 2003), or a plateau after a certain difficulty level (Marois & Ivanoff, 2005;Todd & Marois, 2004;Mitchell & Cusack, 2008). For example, Linden et al. (2003) and Callicott et al. (1999) found that the frontal-parietal network initially showed increased activation with increased working memory load, but decreased in the highest load condition close or beyond the limit of capacity. In our data there was no suggestion of an inverted-U profile; if anything, in some conditions there was a decrease in MD activity over the first few difficulty levels (e.g. Experiment 2, coherence condition). Our data suggest no decrease of MD activity as sensory limits make a task impossible to perform well.
One factor affecting MD recruitment might be advance knowledge of difficulty level. The neural basis of expectation in perceptual tasks has been shown to involve top-down modulation of frontal and parietal cortices to enhance sensory processing in the visual cortex (Giesbrecht, Weissman, Woldorff, & Mangun, 2006;Kastner, Pinsk, De Weerd, Desimone, & Ungerleider, 1999;Kok, Jehee, & de Lange, 2012;Sylvester, Shulman, Jack, & Corbetta, 2009). Furthermore, Manelis and Reder (2015) recently demonstrated using MVPA that the regions involved in a working memory task are the same regions that contain information about the upcoming task difficulty during task preparation. It is therefore possible in our study that participants in the blocked group could have decided to increase attentional effort in an attempt to compensate for anticipated perceptual difficulty. Our data, however, suggested little notable difference between mixed and blocked conditions. Activity across the MD network is increased by many different kinds of cognitive demand (Duncan & Owen, 2000;Fedorenko et al., 2013). In contrast to this "multiple demand" pattern, the present results show little or no consistent effect of sensory manipulations in a simple motion coherence task. As suggested by Han and Marois (2013), results may reflect the degree to which performance can be improved by increasing attentional investment.
When simple sensory decisions are largely data-limited, decreased accuracy cannot be compensated by increased attention, leading to little or no enhancement of MD activity. |
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