The expansion of agriculture has shaped the recent evolutionary history of a specialized squash pollinator.

The expansion of agriculture is responsible for the mass conversion of biologically diverse natural environments into managed agroecosystems dominated by a handful of genetically homogeneous crop species. Agricultural ecosystems typically have very different abiotic and ecological conditions from those they replaced and create potential niches for those species that are able to exploit the abundant resources offered by crop plants. While there are well-studied examples of crop pests that have adapted into novel agricultural niches, the impact of agricultural intensification on the evolution of crop mutualists such as pollinators is poorly understood. We combined genealogical inference from genomic data with archaeological records to demonstrate that the Holocene demographic history of a wild specialist pollinator of Cucurbita (pumpkins, squashes, and gourds) has been profoundly impacted by the history of agricultural expansion in North America. Populations of the squash bee Eucera pruinosa experienced rapid growth in areas where agriculture intensified within the past 1,000 y, suggesting that the cultivation of Cucurbita in North America has increased the amount of floral resources available to these bees. In addition, we found that roughly 20% of this bee species' genome shows signatures of recent selective sweeps. These signatures are overwhelmingly concentrated in populations from eastern North America where squash bees were historically able to colonize novel environments due to human cultivation of Cucurbita pepo and now exclusively inhabit agricultural niches. These results suggest that the widespread cultivation of crops can prompt adaptation in wild pollinators through the distinct ecological conditions imposed by agricultural environments.

Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae).

One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard species Norops brasiliensis (Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation in N. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets.

The use and misuse of regression models in landscape genetic analyses.

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.

Adding landscape genetics and individual traits to the ecosystem function paradigm reveals the importance of species functional breadth.

Animal pollination mediates both reproduction and gene flow for the majority of plant species across the globe. However, past functional studies have focused largely on seed production; although useful, this focus on seed set does not provide information regarding species-specific contributions to pollen-mediated gene flow. Here we quantify pollen dispersal for individual pollinator species across more than 690 ha of tropical forest. Specifically, we examine visitation, seed production, and pollen-dispersal ability for the entire pollinator community of a common tropical tree using a series of individual-based pollinator-exclusion experiments followed by molecular-based fractional paternity analyses. We investigate the effects of pollinator body size, plant size (as a proxy of floral display), local plant density, and local plant kinship on seed production and pollen-dispersal distance. Our results show that while large-bodied pollinators set more seeds per visit, small-bodied bees visited flowers more frequently and were responsible for more than 49% of all long-distance (beyond 1 km) pollen-dispersal events. Thus, despite their size, small-bodied bees play a critical role in facilitating long-distance pollen-mediated gene flow. We also found that both plant size and local plant kinship negatively impact pollen dispersal and seed production. By incorporating genetic and trait-based data into the quantification of pollination services, we highlight the diversity in ecological function mediated by pollinators, the influential role that plant and population attributes play in driving service provision, and the unexpected importance of small-bodied pollinators in the recruitment of plant genetic diversity.

Seasonal Food Scarcity Prompts Long-Distance Foraging by a Wild Social Bee.

Foraging is an essential process for mobile animals, and its optimization serves as a foundational theory in ecology and evolution; however, drivers of foraging are rarely investigated across landscapes and seasons. Using a common bumblebee species from the western United States (Bombus vosnesenskii), we ask whether seasonal decreases in food resources prompt changes in foraging behavior and space use. We employ a unique integration of population genetic tools and spatially explicit foraging models to estimate foraging distances and rates of patch visitation for wild bumblebee colonies across three study regions and two seasons. By mapping the locations of 669 wild-caught individual foragers, we find substantial variation in colony-level foraging distances, often exhibiting a 60-fold difference within a study region. Our analysis of visitation rates indicates that foragers display a preference for destination patches with high floral cover and forage significantly farther for these patches, but only in the summer, when landscape-level resources are low. Overall, these results indicate that an increasing proportion of long-distance foraging bouts take place in the summer. Because wild bees are pollinators, their foraging dynamics are of urgent concern, given the potential impacts of global change on their movement and services. The behavioral shift toward long-distance foraging with seasonal declines in food resources suggests a novel, phenologically directed approach to landscape-level pollinator conservation and greater consideration of late-season floral resources in pollinator habitat management.

Sympatric serpentine endemic Monardella (Lamiaceae) species maintain habitat differences despite hybridization.

Ecological differentiation and genetic isolation are thought to be critical in facilitating coexistence between related species, but the relative importance of these phenomena and the interactions between them are not well understood. Here, we examine divergence in abiotic habitat affinity and the extent of hybridization and introgression between two rare species of Monardella (Lamiaceae) that are both restricted to the same serpentine soil exposure in California. Although broadly sympatric, they are found in microhabitats that differ consistently in soil chemistry, slope, rockiness and vegetation. We identify one active hybrid zone at a site with intermediate soil and above-ground characteristics, and we document admixture patterns indicative of extensive and asymmetric introgression from one species into the other. We find that genetic distance among heterospecific populations is related to geographic distance, such that the extent of apparent introgression is partly explained by the spatial proximity to the hybrid zone. Our work shows that plant species can maintain morphological and ecological integrity in the face of weak genetic isolation, intermediate habitats can facilitate the establishment of hybrids, and that the degree of apparent introgression a population experiences is related to its geographic location rather than its local habitat characteristics.

Beekeeping practices and geographic distance, not land use, drive gene flow across tropical bees.

Across the globe, wild bees are threatened by ongoing natural habitat loss, risking the maintenance of plant biodiversity and agricultural production. Despite the ecological and economic importance of wild bees and the fact that several species are now managed for pollination services worldwide, little is known about how land use and beekeeping practices jointly influence gene flow. Using stingless bees as a model system, containing wild and managed species that are presumed to be particularly susceptible to habitat degradation, here we examine the main drivers of tropical bee gene flow. We employ a novel landscape genetic approach to analyse data from 135 populations of 17 stingless bee species distributed across diverse tropical biomes within the Americas. Our work has important methodological implications, as we illustrate how a maximum-likelihood approach can be applied in a meta-analysis framework to account for multiple factors, and weight estimates by sample size. In contrast to previously held beliefs, gene flow was not related to body size or deforestation, and isolation by geographic distance (IBD) was significantly affected by management, with managed species exhibiting a weaker IBD than wild ones. Our study thus reveals the critical importance of beekeeping practices in shaping the patterns of genetic differentiation across bee species. Additionally, our results show that many stingless bee species maintain high gene flow across heterogeneous landscapes. We suggest that future efforts to preserve wild tropical bees should focus on regulating beekeeping practices to maintain natural gene flow and enhancing pollinator-friendly habitats, prioritizing species showing a limited dispersal ability.

The exosome complex establishes a barricade to erythroid maturation.

Complex genetic networks control hematopoietic stem cell differentiation into progenitors that give rise to billions of erythrocytes daily. Previously, we described a role for the master regulator of erythropoiesis, GATA-1, in inducing genes encoding components of the autophagy machinery. In this context, the Forkhead transcription factor, Foxo3, amplified GATA-1-mediated transcriptional activation. To determine the scope of the GATA-1/Foxo3 cooperativity, and to develop functional insights, we analyzed the GATA-1/Foxo3-dependent transcriptome in erythroid cells. GATA-1/Foxo3 repressed expression of Exosc8, a pivotal component of the exosome complex, which mediates RNA surveillance and epigenetic regulation. Strikingly, downregulating Exosc8, or additional exosome complex components, in primary erythroid precursor cells induced erythroid cell maturation. Our results demonstrate a new mode of controlling erythropoiesis in which multiple components of the exosome complex are endogenous suppressors of the erythroid developmental program.

Positive density-dependent reproduction regulated by local kinship and size in an understorey tropical tree.

BACKGROUND AND AIMS: Global pollinator declines and continued habitat fragmentation highlight the critical need to understand reproduction and gene flow across plant populations. Plant size, conspecific density and local kinship (i.e. neighbourhood genetic relatedness) have been proposed as important mechanisms influencing the reproductive success of flowering plants, but have rarely been simultaneously investigated. METHODS: We conducted this study on a continuous population of the understorey tree Miconia affinis in the Forest Dynamics Plot on Barro Colorado Island in central Panama. We used spatial, reproductive and population genetic data to investigate the effects of tree size, conspecific neighbourhood density and local kinship on maternal and paternal reproductive success. We used a Bayesian framework to simultaneously model the effects of our explanatory variables on the mean and variance of maternal viable seed set and siring success. KEY RESULTS: Our results reveal that large trees had lower proportions of viable seeds in their fruits but sired more seeds. We documented differential effects of neighbourhood density and local kinship on both maternal and paternal reproductive components. Trees in more dense neighbourhoods produced on average more viable seeds, although this positive density effect was influenced by variance-inflation with increasing local kinship. Neighbourhood density did not have significant effects on siring success. CONCLUSIONS: This study is one of the first to reveal an interaction among tree size, conspecific density and local kinship as critical factors differentially influencing maternal and paternal reproductive success. We show that both maternal and paternal reproductive success should be evaluated to determine the population-level and individual traits most essential for plant reproduction. In addition to conserving large trees, we suggest the inclusion of small trees and the conservation of dense patches with low kinship as potential strategies for strengthening the reproductive status of tropical trees.

Native wildflower plantings support wild bee abundance and diversity in agricultural landscapes across the United States.

Global trends in pollinator-dependent crops have raised awareness of the need to support managed and wild bee populations to ensure sustainable crop production. Provision of sufficient forage resources is a key element for promoting bee populations within human impacted landscapes, particularly those in agricultural lands where demand for pollination service is high and land use and management practices have reduced available flowering resources. Recent government incentives in North America and Europe support the planting of wildflowers to benefit pollinators; surprisingly, in North America there has been almost no rigorous testing of the performance of wildflower mixes, or their ability to support wild bee abundance and diversity. We tested different wildflower mixes in a spatially replicated, multiyear study in three regions of North America where production of pollinator-dependent crops is high: Florida, Michigan, and California. In each region, we quantified flowering among wildflower mixes composed of annual and perennial species, and with high and low relative diversity. We measured the abundance and species richness of wild bees, honey bees, and syrphid flies at each mix over two seasons. In each region, some but not all wildflower mixes provided significantly greater floral display area than unmanaged weedy control plots. Mixes also attracted greater abundance and richness of wild bees, although the identity of best mixes varied among regions. By partitioning floral display size from mix identity we show the importance of display size for attracting abundant and diverse wild bees. Season-long monitoring also revealed that designing mixes to provide continuous bloom throughout the growing season is critical to supporting the greatest pollinator species richness. Contrary to expectation, perennials bloomed in their first season, and complementarity in attraction of pollinators among annuals and perennials suggests that inclusion of functionally diverse species may provide the greatest benefit. Wildflower mixes may be particularly important for providing resources for some taxa, such as bumble bees, which are known to be in decline in several regions of North America. No mix consistently attained the full diversity that was planted. Further study is needed on how to achieve the desired floral display and diversity from seed mixes.

Temporal Variation in Honey Production by the Stingless Bee Melipona subnitida (Hymenoptera: Apidae): Long-Term Management Reveals its Potential as a Commercial Species in Northeastern Brazil.

Even though stingless beekeeping has a great potential as a sustainable development tool, the activity remains essentially informal, technical knowledge is scarce, and management practices lack the sophistication and standardization found in apiculture. Here, we contributed to the further development of stingless beekeeping by investigating the long-term impact of management and climate on honey production and colony survival in the stingless bee Melipona subnitida Ducke (1910). We analyzed a 10-yr record of 155 M. subnitida colonies kept by a commercial honey producer of northeastern Brazil. This constitutes the longest and most accurate record available for a stingless bee. We modeled honey production in relation to time (years), age, management practices (colony division and food supplementation), and climatic factors (temperature and precipitation), and used a model selection approach to identify which factors best explained honey production. We also modeled colony mortality in relation to climatic factors. Although the amount of honey produced by each colony decreased over time, we found that the probability of producing honey increased over the years. Colony divisions decreased honey production, but did not affect honey presence, while supplementary feeding positively affected honey production. In warmer years, the probability of producing honey decreased and the amount of honey produced was lower. In years with lower precipitation, fewer colonies produced honey. In contrast, colony mortality was not affected by climatic factors, and some colonies lived up to nine years, enduring extreme climatic conditions. Our findings provide useful guidelines to improve management and honey production in stingless bees.

Mating frequency estimation and its importance for colony abundance analyses in eusocial pollinators: a case study of Bombus impatiens (Hymenoptera: Apidae).

The genus Bombus (bumble bees) includes approximately 265 species, many of which are in decline in North America and Europe. To estimate colony abundance of bumble bees in natural and agricultural habitats, sibship relationships are often reconstructed from genetic data with the assumption that colonies have 1 monandrous queen. However, some species such as the North American common eastern bumble bee (Bombus impatiens Cresson) can display low levels of polyandry, which may bias estimates of colony abundance based on monandrous sibship reconstructions. To accurately quantify rates of polyandry in wild and commercially mated queens of this species, we empirically estimated mating frequencies using a novel statistical model and genotypes from 730 bees. To genotype individuals, we used a highly polymorphic set of microsatellites on colonies established from 20 wild-caught gynes and 10 commercial colonies. We found multiple fathers in 3 of the wild colonies and 3 of the commercial colonies. This resulted in average effective mating frequencies of 1.075 ±â€…0.18 and 1.154 ±â€…0.25 for wild and commercial colonies, respectively. These findings agree with previous reports of low rates of polyandry for B. impatiens. Using a large empirical dataset, we demonstrate that assuming monandry for colony abundance estimation in species that violate this assumption results in an overestimation of the number of colonies. Our results emphasize the importance of studying mating frequencies in social species of conservation concern and economic importance for the accuracy of colony abundance estimation and for understanding their ecology and sociobiology.

Differential effects of 808-nm light on electron transport chain enzymes in isolated mitochondria: Implications for photobiomodulation initiation.

Photobiomodulation is a term for using low-power red to near-infrared light to stimulate a variety of positive biological effects. Though the scientific and clinical acceptance of PBM as a therapeutic intervention has increased dramatically in recent years, the molecular underpinnings of the effect remain poorly understood. The putative chromophore for PBM effects is cytochrome c oxidase. It is postulated that light absorption at cytochrome c oxidase initiates a signaling cascade involving ATP and generation of reactive oxygen species (ROS), which subsequently results in improved cellular robustness. However, this hypothesis is largely based on inference and indirect evidence, and the precise molecular mechanisms that govern how photon absorption leads to these downstream effects remain poorly understood. We conducted low-power PBM-type light exposures of isolated mitochondria to 808 nm NIR light, at a number of irradiances. NIR exposure was found to enhance the activity of complex IV, depress the activity of complex III, and had no effect on the activity of complex II. Further, examining the dose-response of complex IV we found NIR enhancement did not exhibit irradiance reciprocity, indicating the effect on complex IV may not have direct photochemical basis. In summary, this research presents a novel method to interrogate the earliest stages of PBM in the mitochondria, and a unique window into the corresponding molecular mechanism(s) of induction.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Differential coregulator requirements for function of the hematopoietic transcription factor GATA-1 at endogenous loci.

The critical regulator of hematopoiesis GATA-1 recruits diverse coregulators to chromatin, which mediate transcriptional activation and repression. These coregulators include the cell-type-specific multi-zinc finger protein Friend of GATA-1 (FOG-1), the histone acetyltransferase CREB binding protein (CBP), and the key component of the Mediator complex Med1. While FOG-1 is an established GATA-1 coregulator, the importance of interactions between GATA-1 and other coregulators is poorly understood. Furthermore, whether GATA-1 utilizes multiple coregulators at all loci, or if certain coregulators are dedicated to specific loci is unknown. We compared the capacity of GATA-1 to recruit and utilize FOG-1 and Med1 at activated and repressed target genes. Similar to FOG-1, GATA-1 recruited Med1 to activated genes, and the kinetics of FOG-1 and Med1 recruitment were similar. GATA-1 recruited Med1 in Fog1(-/-) cells, indicating that GATA-1-mediated Med1 recruitment is FOG-1-independent. In contrast to FOG-1, GATA-1 evicted Med1 during transcriptional repression. Whereas knocking-down FOG-1 had catastrophic effects on GATA-1-mediated activation and repression, knocking-down Med1 modestly impaired GATA-1 activity only at select loci. These results illustrate both similarities and differences between GATA-1-mediated recruitment of FOG-1 and Med1 to chromatin, with a fundamental difference being the quantitatively greater requirement for FOG-1.

Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data.

BACKGROUND: The site frequency spectrum summarizes the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping. RESULTS: Here we design and implement a method to efficiently and accurately estimate the multidimensional joint site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximizes a likelihood function that represents the probability of the sequencing data observed given a multidimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximization algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. On the basis of extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen Neonectria neomacrospora, results recapitulate the patterns of population differentiation generated using the original high-coverage data. CONCLUSION: The new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage datasets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.

Efficient ancestry and mutation simulation with msprime 1.0.

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Continuous assessment of metabolic activity of mitochondria using resonance Raman microspectroscopy.

Dysfunctional mitochondrial activity can lead to a variety of different diseases. As such, there exists a need to quantify changes in mitochondria function as it relates to these specific diseased states. Here, we present the use of resonance Raman (RR) spectroscopy as a tool to determine changes in isolated mitochondrial activity. RR spectroscopy, using 532 nm as the excitation source, specifically provides information on the reduction and oxidation (RedOx) state of cytochrome c, which is determined by the activity of protein complexes in the electron transport chain (ETC). In this model, injection of the substrate succinate into the mitochondrial sample is used to drive the ETC, which causes a subsequent change in cytochrome c RedOx state. This change in RedOx state is tracked by RR spectroscopy. This tool gives real-time information on the rise and fall of the amount of reduced cytochrome c within the mitochondrial sample, providing a method for rapid assessment of mitochondrial metabolism that has broad applications in both basic science and medical research.

Transient absorption spectroscopy to explore cellular pathways to photobiomodulation.

Photobiomodulation (PBM) describes the use of low irradiance light in the red to near-infrared wavelength range to stimulate biological effects in tissue, and many biological and spectroscopic techniques are used to study PBM. However, these techniques focus on the products or downstream effects rather than the electronic transitions that initiate the PBM processes. This study presents a novel approach to studying low irradiance light exposures on individual proteins and/or protein complexes by combining a continuous wave (CW) laser diode with femtosecond transient absorption spectroscopy (TAS), coined here as CW-TAS, and tests the system on reduced cytochrome c (Cyt c) for proof of principle. TAS was conducted using a 532-nm excitation pump beam and a 350-600 nm supercontinuum probe. CW laser diodes with wavelengths of 450 nm, 635 nm, and 808 nm were interchangeably fiber coupled into the HELIOS Fire. Samples of Cyt c were tested by TAS using a pump power of 15 µW, both with and without CW exposure. CW exposures were carried out with irradiances of 1.60 and 3.20 mW/cm2, except for 808 nm, which was only tested at 1.60 mW/cm2. Both kinetic and global analyses were performed on the TAS data and the time constants for sets with and without CW exposures were compared. The TAS data for Cyt c with the full dosage of CW exposures did not alter the TAS data distinguishably from the control data. No new electronic transient signals were observed beyond the background when testing Cyt c with the CW exposures. Kinetic analysis confirmed that existing transients did not deviate beyond uncertainty. Global time constants for Cyt c were calculated to be 0.25 ± 0.03 ps and 5.1 ± 0.3 ps for the control study, and the time constants for the CW exposed Cyt c were not significantly different. This study concludes that CW irradiation, at doses delivered, does not alter the transient absorption data of Cyt c. The CW-TAS method provides a new tool for studying PBM effects in other proteins and protein complexes that might respond to the CW wavelengths, such as Complex IV, in future studies.

Mammalian complex III heme dynamics studied with pump-probe spectroscopy and red light illuminations.

The electronic or molecular mechanisms that initiate photobiomodulation (PBM) in cells are not yet fully understood. The porcine complex III (C-III) of the electron transport chain was characterized with transient absorption spectroscopy (TAS). We then applied our recently developed continuous wave laser coupled TAS procedure (CW-TAS) to investigate the effect of red light irradiances on the heme dynamics of C-III in its c1 reduced state. The time constants were found to be 3.3 ± 0.3 ps for vibrational cooling of the oxidized state and 4.9 ± 0.4 ps for rebinding of the photodissociated axial ligand of the c1 reduced state. The analysis of the CW-TAS procedure yielded no significant changes in the C-III heme dynamics. We rule out the possibility of 635 nm CW light at 4.7 mW/cm2 inducing a PBM effect on the heme dynamic of C-III, specifically with the photodissociation of its axial ligand.