Hyperspectral imaging of snow algae and green algae from aeroterrestrial habitats

Holzinger, Andreas; Allen, Michael C.; Deheyn, Dimitri D.

doi:10.1016/j.jphotobiol.2016.07.001

Cited by 27 publications

(24 citation statements)

References 45 publications

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“…Given the differences we observed in reflecting platelet architectures of iridophores from stripes versus interstripes, however, we reasoned that reflected spectra might be intrinsic properties of iridophore subtypes. Consistent with this hypothesis, we found close matches between spectra predicted from simulations based on a Monte Carlo transfer matrix 33 (with morphometic data derived from cryo-SEM) and empirical reflectance spectra recorded for individual cells by hyperspectral imaging microscopy 34 ( Fig. 3f, g ).…”

Section: Resultssupporting

confidence: 81%

In situdifferentiation of iridophore crystallotypes underlies zebrafish stripe patterning

Gur

Bain

Johnson

et al. 2020

Preprint

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22Skin color patterns are ubiquitous in nature, evolve rapidly, and impact social 23 behavior 1 , predator avoidance 2 , and protection from ultraviolet irradiation 3 . A 24 leading model system for vertebrate skin patterning is the zebrafish 4-7 ; its 25 alternating blue stripes and yellow interstripes depend on guanine crystal-26 containing cells called iridophores that reflect light. It was suggested that the 27 zebrafish's alternating color pattern arises from a single type of iridophore 28 migrating differentially to stripes and interstripes 7-9 . When we tracked iridophores, 29 however, we found they did not migrate between stripes and interstripes but 30 instead differentiated and proliferated in place based on their micro-environment. 31RNA seq analysis further revealed stripe and interstripe iridophores had different 32 transcriptomic states, while cryogenic scanning electron microscopy and micro-33 X-ray diffraction showed they had different guanine crystal organizations and 34 responsiveness to norepinephrine, all indicating that stripe and interstripe 35 iridophores are different cell types. Based on these results, we present a new 36 model of skin patterning in zebrafish in which distinct iridophore crystallotypes 37 containing specialized, physiologically responsive, subcellular organelles arise in 38 stripe and interstripe zones by in situ differentiation. In this model, pattern 39 phenotype depends not only on interactions among pigment cells that affect their 40 arrangements, but also on factors that specify subcellular organization and 41 physiological responsiveness of specialized organelles. 42 43 Introduction 1 Biological patterning is ubiquitous in nature, but mechanisms underlying its 2 establishment and maintenance have been well-documented in only a few instances that 3 are unlikely to represent the full spectrum of pattern-forming systems 6,10 . Indeed, 4 patterning can arise in response to graded positional information or by self-organization 5 of interacting cells, and it can require alternative specification of cell-types from a 6 common progenitor or sorting-out of cells that are heterogeneous already. Elucidating 7 the mechanisms required to pattern cells in diverse tissues and organs is fundamental to 8 understanding development and how phenotypes evolve.9The alternating dark (blue) and light (yellow) pigmented stripe pattern of adult 10 zebrafish Danio rerio (Fig. 1a) is a useful model for dissecting patterning 11 mechanisms 4,5,7,11,12 . Cells within the dark stripes include black pigment-containing 12 melanophores; cells in the light stripes (known as "interstripes") include orange-pigment 13 containing xanthophores; and both dark stripes and light interstripes contain specialized 14 cells called iridophores 13,14 . Iridophores are the major players for skin pattern 15 establishment and reiteration in zebrafish. They behave as reflective cells, exhibiting 16 angular-dependent changes in hue-iridescence-owing to membrane-bound reflecting 17 platelets of crystalline guanine 14-16...

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Section: Resultssupporting

confidence: 81%

In situdifferentiation of iridophore crystallotypes underlies zebrafish stripe patterning

Gur

Bain

Johnson

et al. 2020

Preprint

Self Cite

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“…This could be used to extract ecological information from remotely sensed spectra, since pigmentation can change in response to environmental conditions [ Remias et al ., , ]. In particular, C. nivalis in its developmental stage contains fewer carotenoids and has a greener coloration; mature cells accumulate secondary carotenoids and become orange‐red [ Holzinger et al ., ]. We therefore predicted the spectral reflectance of a range of algal blooms and identified “signature” reflectance patterns.…”

Section: Resultsmentioning

confidence: 99%

A predictive model for the spectral “bioalbedo” of snow

et al. 2017

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We present the first physical model for the spectral “bioalbedo” of snow, which predicts the spectral reflectance of snowpacks contaminated with variable concentrations of red snow algae with varying diameters and pigment concentrations and then estimates the effect of the algae on snowmelt. The biooptical model estimates the absorption coefficient of individual cells; a radiative transfer scheme calculates the spectral reflectance of snow contaminated with algal cells, which is then convolved with incoming spectral irradiance to provide albedo. Albedo is then used to drive a point‐surface energy balance model to calculate snowpack melt rate. The model is used to investigate the sensitivity of snow to algal biomass and pigmentation, including subsurface algal blooms. The model is then used to recreate real spectral albedo data from the High Sierra (CA, USA) and broadband albedo data from Mittivakkat Gletscher (SE Greenland). Finally, spectral “signatures” are identified that could be used to identify biology in snow and ice from remotely sensed spectral reflectance data. Our simulations not only indicate that algal blooms can influence snowpack albedo and melt rate but also highlight that “indirect” feedback related to their presence are a key uncertainty that must be investigated.

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“…The detected carotenoids potentially play a key role in energy dissipation in chloroplasts under high light conditions (Demmig‐Adams & Adams, ; Remias et al ., ). Higher concentrations of astaxanthin esters in red blooms have also been reported elsewhere (Remias & Lütz, ; Lutz et al ., ), the production of which can be dependent on developmental stage (Holzinger et al ., ) or upon environmental stresses, in particular light intensity and nutrient deficiency (Remias et al ., , ; Lutz et al ., ; Minhas et al ., ).…”

Section: Discussionmentioning

confidence: 99%

Snow algae communities in Antarctica: metabolic and taxonomic composition

et al. 2019

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Summary Snow algae are found in snowfields across cold regions of the planet, forming highly visible red and green patches below and on the snow surface. In Antarctica, they contribute significantly to terrestrial net primary productivity due to the paucity of land plants, but our knowledge of these communities is limited. Here we provide the first description of the metabolic and species diversity of green and red snow algae communities from four locations in Ryder Bay (Adelaide Island, 68°S), Antarctic Peninsula. During the 2015 austral summer season, we collected samples to measure the metabolic composition of snow algae communities and determined the species composition of these communities using metabarcoding. Green communities were protein‐rich, had a high chlorophyll content and contained many metabolites associated with nitrogen and amino acid metabolism. Red communities had a higher carotenoid content and contained more metabolites associated with carbohydrate and fatty acid metabolism. Chloromonas , Chlamydomonas and Chlorella were found in green blooms but only Chloromonas was detected in red blooms. Both communities also contained bacteria, protists and fungi. These data show the complexity and variation within snow algae communities in Antarctica and provide initial insights into the contribution they make to ecosystem functioning.

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Hyperspectral imaging of snow algae and green algae from aeroterrestrial habitats

Cited by 27 publications

References 45 publications

In situdifferentiation of iridophore crystallotypes underlies zebrafish stripe patterning

In situdifferentiation of iridophore crystallotypes underlies zebrafish stripe patterning

A predictive model for the spectral “bioalbedo” of snow

Snow algae communities in Antarctica: metabolic and taxonomic composition

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