Toxic Habits: An Analysis of General Trends and Biases in Snake Venom Research

Biases in snake venom research have been partially identified but seldomly quantified. Using the Google Scholar web search engine, we collected a total of 267 articles published between 1964 and 2021, and reviewed them to assess the main trends in this field of study. We developed a 4-category classification of the harmful potential of each of the 298 snake species retrieved from the analysed publications, and tested whether taxonomy, realm of origin, and/or assigned hazard category could affect how often each of them appeared in the articles considered. Overall, viperids were significantly more represented than any other snake taxon retrieved. The Neotropics were the most represented biogeographic realm for number of studied species, whereas information about the country of origin of the analysed specimens was often incomplete. The vast majority of the publications focused on snake venom characterisation, whereas more ecology-related topics were rarely considered. Hazard category and biogeographic realm of origin of each species had a significant effect on the number of articles dedicated to it, suggesting that a snake's harmful potential and place of origin influence its popularity in venom studies. Our analysis showed an overall positive trend in the number of snake venom studies published yearly, but also underlined severe neglect of snake families of supposedly minor medical relevance (e.g., Atractaspididae), underrepresentation of some of the areas most impacted by snakebite (i.e., Indomalayan and Afrotropic realms), and limited interest in the ecological and functional context of snake venom.

Reflections on the past, present and future of developmental biology

Developmental Biology embodies some of the most fundamental questions in Biology and can trace its roots back to several thousand years ago; the last 100 years have been particularly extraordinary. In part the advances have been fuelled by new technical advances and knowledge in many other areas, which have contributed to shaping the field as truly interdisciplinary. During those 100 years some of our predecessors identified some key questions and a few important principles especially by trying to find general rules that govern what cells are able to do and how they choose between different options, as well as principles of experimental design that can be used to uncover those rules even before we know their physicochemical underpinnings. But the field has been changing rapidly in the last two decades. Here I present a brief overview of some of the changes that have taken place over the last Century and a personal view of current directions. The picture that emerges is of some dark clouds on the horizon, so this is also a call to arms for our colleagues to try to regain what the field has been losing.

Genetic Causation in Complex Regulatory Systems: An Integrative Dynamic Perspective

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype-phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference-making causes of phenotypes is re-examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This review argues that it is appropriate to treat genes as specific actual difference-makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause-and-effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes.

Network architecture and sex chromosome turnovers: Do epistatic interactions shape patterns of sex chromosome replacement?

Recent studies have revealed an astonishing diversity of sex chromosomes in many vertebrate lineages, prompting questions about the mechanisms of sex chromosome turnover. While there is considerable population genetic theory about the evolutionary forces promoting sex chromosome replacement, this theory has not yet been integrated with our understanding of the molecular and developmental genetics of sex determination. Here, we review recent data to examine four questions about how the structure of gene networks influences the evolution of sex determination. We argue that patterns of epistasis, arising from the structure of genetic networks, may play an important role in regulating the rates and patterns of sex chromosome replacement.

From personalised nutrition to precision medicine: the rise of consumer genomics and digital health

Advances in genomics generated the concept that a better understanding of individual characteristics, e.g. genotype, will lead to improved tailoring of pharmaceutical and nutritional therapies. Subsequent developments in proteomics and metabolomics, in addition to wearable technologies for tracking parameters, such as dietary intakes, physical activity, heart rate and blood glucose, have further driven this idea. Alongside these innovations, there has been a rapid rise in companies offering direct-to-consumer genetic and/or microbiome testing, in combination with the marketing of personalised nutrition services. Key scientific questions include how disparate datasets are integrated, how accurate are current predictions and how these may be developed in the future. In this regard, lessons can be learned from systems biology, which aims both to integrate data from different levels of organisation (e.g. genomic, proteomic and metabolomic) and predict the emergent behaviours of biological systems or organisms as a whole. The present paper reviews the origins and recent advancement of 'big data' and systems approaches in medicine and nutrition. Conclusions are that systems integration of multiple technologies has generated mechanistic insights and informed the evolution of precision medicine and personalised nutrition. Pertinent ethical issues include who is entitled to access new technologies and how commercial companies are storing, using and/or re-mining consumer data. Questions about efficacy (both long-term behavioural change and health outcomes), cost-benefit and impacts on health inequalities remain to be fully addressed.

From molecules to macroevolution: Venom as a model system for evolutionary biology across levels of life

Biological systems are inherently hierarchical. Consequently, any field which aims to understand an aspect of biology holistically requires investigations at each level of the hierarchy of life, and venom research is no exception. This article aims to illustrate the structure of the field in light of a ‘levels of life’ perspective. In doing so, I highlight how traditional fields and approaches fit into this structure as focussing on describing levels or investigating links between levels, and emphasise where implicit assumptions are made due to lack of direct information. Taking a ‘levels of life’ perspective to venom research enables us to understand the complementarity of different research programmes and identify avenues for future research. Moreover, it provides a broader view that, in itself, shows how new questions can be addressed. For instance, understanding how adaptations develop and function from molecular to organismal scales, and what the consequences are of those adaptations at scales from molecular to macroevolutionary, is a general question relevant to a great deal of biology. As a trait which is molecular in nature and has clearer and more direct links between genotype and phenotype than many other traits, venom provides a relatively simple system to address such questions. Furthermore, because venom is also diverse at each level of life, the complexity within the hierarchical structure provides variation that enables powerful analytical approaches to answering questions. As a result, venom provides an excellent model system for understanding big questions in evolutionary biology.

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Venom is a molecular trait used directly in fitness-relevant ecological interaction.

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Venom is consequently an ideal model system for evolutionary biology.

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A ‘levels of life’ perspective is well suited to research in venom biology.

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This structure of the field provides many advantages to guide future studies.

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Clinical implications can arise from studies of venom at all levels of life.

Proton Nuclear Magnetic Resonance Metabolomics Corroborates Serine Hydroxymethyltransferase as the Primary Target of 2-Aminoacrylate in a ridA Mutant of Salmonella enterica

The accumulation of the reactive enamine intermediate 2-aminoacrylate (2AA) elicits global metabolic stress in many prokaryotes and eukaryotes by simultaneously damaging multiple pyridoxal 5′-phosphate (PLP)-dependent enzymes. This work employed ¹H NMR to expand our understanding of the consequence(s) of 2AA stress on metabolite pools and effectively identify the metabolic changes stemming from one damaged target: GlyA. This study shows that nutrient supplementation during ¹H NMR metabolomics experiments can disentangle complex metabolic outcomes stemming from a general metabolic stress. Metabolomics shows great potential to complement classical reductionist approaches to cost-effectively accelerate the rate of progress in expanding our global understanding of metabolic network structure and physiology. To that end, this work demonstrates the utility in implementing nutrient supplementation and genetic perturbation into metabolomics workflows as a means to connect metabolic outputs to physiological phenomena and establish causal relationships.

The reactive intermediate deaminase RidA (EC 3.5.99.10) is conserved across all domains of life and deaminates reactive enamine species. When Salmonella entericaridA mutants are grown in minimal medium, 2-aminoacrylate (2AA) accumulates, damages several pyridoxal 5′-phosphate (PLP)-dependent enzymes, and elicits an observable growth defect. Genetic studies suggested that damage to serine hydroxymethyltransferase (GlyA), and the resultant depletion of 5,10-methelenetetrahydrofolate (5,10-mTHF), was responsible for the observed growth defect. However, the downstream metabolic consequence from GlyA damage by 2AA remains relatively unexplored. This study sought to use untargeted proton nuclear magnetic resonance (¹H NMR) metabolomics to determine whether the metabolic state of an S. entericaridA mutant was accurately reflected by characterizing growth phenotypes. The data supported the conclusion that metabolic changes in a ridA mutant were due to the IlvA-dependent generation of 2AA, and that the majority of these changes were a consequence of damage to GlyA. While many of the metabolic differences for a ridA mutant could be explained, changes in some metabolites were not easily modeled, suggesting that additional levels of metabolic complexity remain to be unraveled.

IMPORTANCE The accumulation of the reactive enamine intermediate 2-aminoacrylate (2AA) elicits global metabolic stress in many prokaryotes and eukaryotes by simultaneously damaging multiple pyridoxal 5′-phosphate (PLP)-dependent enzymes. This work employed ¹H NMR to expand our understanding of the consequence(s) of 2AA stress on metabolite pools and effectively identify the metabolic changes stemming from one damaged target: GlyA. This study shows that nutrient supplementation during ¹H NMR metabolomics experiments can disentangle complex metabolic outcomes stemming from a general metabolic stress. Metabolomics shows great potential to complement classical reductionist approaches to cost-effectively accelerate the rate of progress in expanding our global understanding of metabolic network structure and physiology. To that end, this work demonstrates the utility in implementing nutrient supplementation and genetic perturbation into metabolomics workflows as a means to connect metabolic outputs to physiological phenomena and establish causal relationships.