Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Impact of Heavy Metals on Cold Acclimation of Salix viminalis Roots

In nature, plants are exposed to a range of climatic conditions. Those negatively impacting plant growth and survival are called abiotic stresses. Although abiotic stresses have been extensively studied separately, little is known about their interactions. Here, we investigate the impact of long-term mild metal exposure on the cold acclimation of Salix viminalis roots using physiological, transcriptomic, and proteomic approaches. We found that, while metal exposure significantly affected plant morphology and physiology, it did not impede cold acclimation. Cold acclimation alone increased glutathione content and glutathione reductase activity. It also resulted in the increase in transcripts and proteins belonging to the heat-shock proteins and related to the energy metabolism. Exposure to metals decreased antioxidant capacity but increased catalase and superoxide dismutase activity. It also resulted in the overexpression of transcripts and proteins related to metal homeostasis, protein folding, and the antioxidant machinery. The simultaneous exposure to both stressors resulted in effects that were not the simple addition of the effects of both stressors taken separately. At the antioxidant level, the response to both stressors was like the response to metals alone. While this should have led to a reduction of frost tolerance, this was not observed. The impact of the simultaneous exposure to metals and cold acclimation on the transcriptome was unique, while at the proteomic level the cold acclimation component seemed to be dominant. Some genes and proteins displayed positive interaction patterns. These genes and proteins were related to the mitigation and reparation of oxidative damage, sugar catabolism, and the production of lignans, trehalose, and raffinose. Interestingly, none of these genes and proteins belonged to the traditional ROS homeostasis system. These results highlight the importance of the under-studied role of lignans and the ROS damage repair and removal system in plants simultaneously exposed to multiple stressors.

The Soybean Expression Atlas v2: A comprehensive database of over 5000 RNA-seq samples

Soybean is a crucial crop worldwide, used as a source of food, feed, and industrial products due to its high protein and oil content. Previously, the rapid accumulation of soybean RNA-seq data in public databases and the computational challenges of processing raw RNA-seq data motivated us to develop the Soybean Expression Atlas, a gene expression database of over a thousand RNA-seq samples. Over the past few years, our database has allowed researchers to explore the expression profiles of important gene families, discover genes associated with agronomic traits, and understand the transcriptional dynamics of cellular processes. Here, we present the Soybean Expression Atlas v2, an updated version of our database with a fourfold increase in the number of samples, featuring transcript- and gene-level transcript abundance matrices for 5481 publicly available RNA-seq samples. New features in our database include the availability of transcript-level abundance estimates and equivalence classes to explore differential transcript usage, abundance estimates in bias-corrected counts to increase the accuracy of differential gene expression analyses, a new web interface with improved data visualization and user experience, and a reproducible and scalable pipeline available as an R package. The Soybean Expression Atlas v2 is available at https://soyatlas.venanciogroup.uenf.br/, and it will accelerate soybean research, empowering researchers with high-quality and easily accessible gene expression data.

Metabolism of pancreatic neuroendocrine tumors: what can omics tell us?

Introduction

Reprogramming of cellular metabolism is now a hallmark of tumorigenesis. In recent years, research on pancreatic neuroendocrine tumors (pNETs) has focused on genetic and epigenetic modifications and related signaling pathways, but few studies have been devoted to characterizing the metabolic profile of these tumors. In this review, we thoroughly investigate the metabolic pathways in pNETs by analyzing the transcriptomic and metabolomic data available in the literature.

Methodology

We retrieved and downloaded gene expression profiles from all publicly available gene set enrichments (GSE43797, GSE73338, and GSE117851) to compare the differences in expressed genes based on both the stage and MEN1 mutational status. In addition, we conducted a systematic review of metabolomic data in NETs.

Results

By combining transcriptomic and metabolomic approaches, we have identified a distinctive metabolism in pNETs compared with controls without pNETs. Our analysis showed dysregulations in the one-carbon, glutathione, and polyamine metabolisms, fatty acid biosynthesis, and branched-chain amino acid catabolism, which supply the tricarboxylic acid cycle. These targets are implicated in pNET cell proliferation and metastasis and could also have a prognostic impact. When analyzing the profiles of patients with or without metastasis, or with or without MEN1 mutation, we observed only a few differences due to the scarcity of published clinical data in the existing research. Consequently, further studies are now necessary to validate our data and investigate these potential targets as biomarkers or therapeutic solutions, with a specific focus on pNETs.

Moving Research-Based Learning in Life Sciences Upstream, and Beyond Borders: An International Group Research Project for High School Youth

International cooperation beyond borders, institutions, and intergenerationally is an important aspect of science and research-based learning. Timing of learning also matters. Early exposure to group research-based learning can potentially have lasting positive impacts on youth and their careers in life sciences. Here, we report our work on the International Group Project (IGP), which builds on the International Biology Olympiad (IBO) organized in Yerevan, Armenia, in 2022. The IBO is an annual international competition for high school students held since 1990 around the world. We envisioned the IGP as a novel opportunity for life sciences research-based education among youth. We formed diverse IGP research teams 2 months before the IBO, and comprised high school students from 32 countries, communicating in a digital environment via videoconferencing. Each team formulated a research question in an IGP theme from five domains of life sciences: "Biomedicine," "Molecular and cell biology," "Bioinformatics and Artificial Intelligence," "Bionics and Biomimicry," "Across Species." Subsequently, team members collectively solved their research question by applying life sciences methodologies under supervision from a facilitator scientist. Each team created a poster based on their research and presented in-person to the public at a satellite activity at the IBO. A special subcommittee of the IBO International Jury graded posters and allocated prizes based on scientific ingenuity and presentation quality. This experience from the IGP lends evidence to the feasibility of research-based learning in life sciences for high school youth beyond borders. Moving research-based learning upstream and internationally is well poised to advance 21st century life sciences from both interdisciplinary and intergenerational standpoints. The historic impact of the COVID-19 pandemic suggests that youth engagement in research-based learning and innovation in life sciences is timely.

Characterization of Lipid Alterations by Oncogenic PIK3CA Mutations Using Untargeted Lipidomics in Breast Cancer

Lipids play crucial biological roles in health and disease, including in cancers. The phosphatidylinositol 3-kinase (PI3K) signaling pathway is a pivotal promoter of cell growth and proliferation in various types of cancer. The somatic mutations in PIK3CA, the gene coding for the catalytic subunit p110α of PI3K, are frequently present in cancer cells, including breast cancer. Although the most prominent mutants, represented by single amino acid substitutions in the helical domain in exon 9 (E545K) and the kinase domain in exon 20 (H1047R) are known to cause a gain of PI3K function, activate AKT signaling and induce oncogenic transformation, the effect of these mutations on cellular lipid profiles has not been studied. We carried out untargeted lipidomics using liquid chromatography-tandem mass spectrometry to detect the lipid alterations in mammary gland epithelial MCF10A cells with isogenic knockin of these mutations. A total of 536 species of lipids were analyzed. We found that the levels of monosialogangliosides, signaling molecules known to enhance cell motility through PI3K/AKT pathway, were significantly higher in both mutants. In addition, triglycerides and ceramides, lipid molecules known to be involved in promoting lipid droplet production, cancer cell migration and invasion, were increased, whereas lysophosphatidylcholines and phosphatidylcholines that are known to inhibit cancer cell motility were decreased in both mutants. Our results provide novel insights into a potential link between altered lipid profile and carcinogenesis caused by the PIK3CA hotspot mutations. In addition, we suggest untargeted lipidomics offers prospects for precision/personalized medicine by unpacking new molecular substrates of cancer biology.

Identifying the Common Cell-Free DNA Biomarkers across Seven Major Cancer Types

Blood-based detection of circulating cell-free DNA (cfDNA) is a non-invasive and easily accessible method for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to developing clinical biomarkers. For example, cfDNA with genetic alterations often composes a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from healthy populations will be important for cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in a small number of cfDNA-based cancer tests. We hypothesize that the combination of diverse types of cancer studies on cfDNA will provide us with a new perspective on the identification of low-frequency genetic variants across cancer types for promoting early diagnosis. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritized 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting the membrane, some of which are tumour suppressors, oncogenes, and genes related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as common biomarkers in early cancer diagnosis.

Integrative biology of injury in animals

Mechanical injury is a prevalent challenge in the lives of animals with myriad potential consequences for organisms, including reduced fitness and death. Research on animal injury has focused on many aspects, including the frequency and severity of wounding in wild populations, the short- and long-term consequences of injury at different biological scales, and the variation in the response to injury within or among individuals, species, ontogenies, and environmental contexts. However, relevant research is scattered across diverse biological subdisciplines, and the study of the effects of injury has lacked synthesis and coherence. Furthermore, the depth of knowledge across injury biology is highly uneven in terms of scope and taxonomic coverage: much injury research is biomedical in focus, using mammalian model systems and investigating cellular and molecular processes, while research at organismal and higher scales, research that is explicitly comparative, and research on invertebrate and non-mammalian vertebrate species is less common and often less well integrated into the core body of knowledge about injury. The current state of injury research presents an opportunity to unify conceptually work focusing on a range of relevant questions, to synthesize progress to date, and to identify fruitful avenues for future research. The central aim of this review is to synthesize research concerning the broad range of effects of mechanical injury in animals. We organize reviewed work by four broad and loosely defined levels of biological organization: molecular and cellular effects, physiological and organismal effects, behavioural effects, and ecological and evolutionary effects of injury. Throughout, we highlight the diversity of injury consequences within and among taxonomic groups while emphasizing the gaps in taxonomic coverage, causal understanding, and biological endpoints considered. We additionally discuss the importance of integrating knowledge within and across biological levels, including how initial, localized responses to injury can lead to long-term consequences at the scale of the individual animal and beyond. We also suggest important avenues for future injury biology research, including distinguishing better between related yet distinct injury phenomena, expanding the subjects of injury research to include a greater variety of species, and testing how intrinsic and extrinsic conditions affect the scope and sensitivity of injury responses. It is our hope that this review will not only strengthen understanding of animal injury but will contribute to building a foundation for a more cohesive field of 'injury biology'.

Systems Biology of COVID-19 and Human Diseases: Beyond a Bird's Eye View, and Toward One Health

As we gaze into the future beyond the current coronavirus disease 2019 (COVID-19) pandemic, there is a need to rethink our priorities in planetary health, research funding, and, importantly, the concepts and unchecked assumptions by which we attempt to understand health and prevent illness. Next-generation quantitative omics technologies promise a more profound and panoptic understanding of the dynamic pathophysiological processes and their aberrations in diverse diseased conditions. Systems biology research is highly relevant for COVID-19, a systemic disease affecting multiple organs and biological pathways. In addition, expanding the concept of health beyond humans so as to capture the importance of ecosystem health and recognizing the interdependence of human, animal, and plant health are enormously relevant and timely in the current historical moment of the pandemic. Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, can affect our body clock, and the circadian aspects of this viral infection and host immunity need to be considered for its effective clinical management. Finally, we need to rethink and expand beyond the false binaries such as humans versus nature, and deploy multiomics systems biology research if we intend to design effective, innovative, and socioecological planetary health interventions to prevent future pandemics and ecological crises. We argue here that juxtaposing ecology and human health sciences scholarship is one of the key emerging tenets of 21st-century integrative biology.

How Can We Advance Integrative Biology Research in Animal Science in 21st Century? Experience at University of Ljubljana from 2002 to 2022

In this perspective analysis, we strive to answer the following question: how can we advance integrative biology research in the 21st century with lessons from animal science? At the University of Ljubljana, Biotechnical Faculty, Department of Animal Science, we share here our three lessons learned in the two decades from 2002 to 2022 that we believe could inform integrative biology, systems science, and animal science scholarship in other countries and geographies. Cultivating multiomics knowledge through a conceptual lens of integrative biology is crucial for life sciences research that can stand the test of diverse biological, clinical, and ecological contexts. Moreover, in an era of the current COVID-19 pandemic, animal nutrition and animal science, and the study of their interactions with human health (and vice versa) through integrative biology approaches hold enormous prospects and significance for systems medicine and ecosystem health.

Inference of an Integrative, Executable Network for Rheumatoid Arthritis Combining Data-Driven Machine Learning Approaches and a State-of-the-Art Mechanistic Disease Map

Rheumatoid arthritis (RA) is a multifactorial, complex autoimmune disease that involves various genetic, environmental, and epigenetic factors. Systems biology approaches provide the means to study complex diseases by integrating different layers of biological information. Combining multiple data types can help compensate for missing or conflicting information and limit the possibility of false positives. In this work, we aim to unravel mechanisms governing the regulation of key transcription factors in RA and derive patient-specific models to gain more insights into the disease heterogeneity and the response to treatment. We first use publicly available transcriptomic datasets (peripheral blood) relative to RA and machine learning to create an RA-specific transcription factor (TF) co-regulatory network. The TF cooperativity network is subsequently enriched in signalling cascades and upstream regulators using a state-of-the-art, RA-specific molecular map. Then, the integrative network is used as a template to analyse patients' data regarding their response to anti-TNF treatment and identify master regulators and upstream cascades affected by the treatment. Finally, we use the Boolean formalism to simulate in silico subparts of the integrated network and identify combinations and conditions that can switch on or off the identified TFs, mimicking the effects of single and combined perturbations.

Using Integrative Biology to Infer Adaptation from Comparisons of Two (or a Few) Species

AbstractPhylogenetic comparative methods represent a major advance in integrative and comparative biology and have allowed researchers to rigorously test for adaptation in a macroevolutionary framework. However, phylogenetic comparative methods require trait data for many species, which is impractical for certain taxonomic groups and trait types. We propose that the philosophical principle of severity can be implemented in an integrative framework to generate strong inference of adaptation in studies that compare only a few populations or species. This approach requires (1) ensuring that the study system contains species that are relatively closely related; (2) formulating a specific, clear, overarching hypothesis that can be subjected to integrative testing across levels of biological organization (e.g., ecology, behavior, morphology, physiology, and genetics); (3) collecting data that avoid statistical underdetermination and thus allow severe tests of hypotheses; and (4) systematically refining and refuting alternative hypotheses. Although difficult to collect for more than a few species, detailed, integrative data can be used to differentiate among several potential agents of selection. In this way, integrative studies of small numbers of closely related species can complement and even improve on broadscale phylogenetic comparative studies by revealing the specific drivers of adaptation.

A new mechanistic approach for the treatment of chronic neuropathic pain with nitrous oxide integrated from a systems biology narrative review

The limitations of the currently available treatments for chronic neuropathic pain highlight the need for safer and more effective alternatives. The authors carried out a focused review using a systems biology approach to integrate the complex mechanisms of nociception and neuropathic pain, and to decipher the effects of nitrous oxide (N₂O) on those pathways, beyond the known effect of N₂O on N-methyl-D-aspartate receptors. This review identified a number of potential mechanisms by which N₂O could impact the processes involved in peripheral and central sensitization. In the ascending pathway, the effects of N₂O include activating TWIK-related K⁺ channel 1 potassium channels on first-order neurons, blocking voltage-dependent calcium channels to attenuate neuronal excitability, attenuating postsynaptic glutamatergic receptor activation, and possibly blocking voltage-dependent sodium channels. In the descending pathway, N₂O induces the release of endogenous opioid ligands and stimulates norepinephrine release. In addition, N₂O may mediate epigenetic changes by inhibiting methionine synthase, a key enzyme involved in DNA and RNA methylation. This could explain why this short-acting analgesic has shown long-lasting anti-pain sensitization effects in animal models of chronic pain. These new hypotheses support the rationale for investigating N₂O, either alone or in combination with other analgesics, for the management of chronic neuropathic pain.

Thermal effects vary predictably across levels of organization: empirical results and theoretical basis

Thermal performance curves have provided a common framework to study the impact of temperature in biological systems. However, few generalities have emerged to date. Here, we combine an experimental approach with theoretical analyses to demonstrate that performance curves are expected to vary predictably with the levels of biological organization. We measured rates of enzymatic reactions, organismal performance and population viability in Drosophila acclimated to different thermal conditions and show that performance curves become narrower with thermal optima shifting towards lower temperatures at higher levels or organization. We then explain these results on theoretical grounds, showing that this pattern reflects the cumulative impact of asymmetric thermal effects that piles up with complexity. These results and the proposed framework are important to understand how organisms, populations and ecological communities might respond to changing thermal conditions.

The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook

Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.

Tspan15 Is a New Stemness-Related Marker in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the second cause of cancer-related deaths worldwide. A clearer understanding of the molecular mechanisms underlying tumor growth and invasiveness remains crucial for developing new therapies. Here, the expression of tetraspanins, a family of plasma membrane organizers involved in tumor progression, has been addressed. Integrative approaches combining transcriptomics and bioinformatics allow demonstrating the induced and heterogeneous expression of Tspan15 in HCC. Tspan15 positive tumors exhibit signatures related to hepatic progenitor cells as well as recurrence of cancer. Immunohistochemistry experiments confirm Tspan15 expression in the subset of HCC expressing stemness-related markers such as EpCAM and Cytokeratin-19. Functional networks reveal that most of these genes expressed in correlation to Tspan15 support cell proliferation. Furthermore, Tspan15 overexpression in the hepatoma cell line HepG2 significantly increases cell proliferation. A quantitative proteomic analysis of the secretome reveals a higher abundance of the protein connective tissue growth factor (CTGF), a pleiotropic matricellular signaling protein. Proteomic profiling of Tspan15 complexes allows identifying numerous membrane proteins including several growth factor receptors. Finally, Tspan15 increases ERK1/2 phosphorylation that directly controls CTGF expression and secretion. In conclusion, Tspan15 is a new stemness-related marker in HCC which exhibits high potential of tumor growth and recurrence.

Food allergy and omics

Food allergy (FA) prevalence has been increasing over the last few decades and is now a global health concern. Current diagnostic methods for FA result in a high number of false-positive results, and the standard of care is either allergen avoidance or use of epinephrine on accidental exposure, although currently with no other approved treatments. The increasing prevalence of FA, lack of robust biomarkers, and inadequate treatments warrants further research into the mechanism underlying food allergies. Recent technological advances have made it possible to move beyond traditional biological techniques to more sophisticated high-throughput approaches. These technologies have created the burgeoning field of omics sciences, which permit a more systematic investigation of biological problems. Omics sciences, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and exposomics, have enabled the construction of regulatory networks and biological pathway models. Parallel advances in bioinformatics and computational techniques have enabled the integration, analysis, and interpretation of these exponentially growing data sets and opens the possibility of personalized or precision medicine for FA.

Matrix

In current biomedicine, omics technologies drive systems-oriented modes of research to achieve a more holistic and personalized view of health and disease. This shift in scientific approach co-occurs with an era of biocapitalism characterized by markets for biomaterial (e.g., DNA, cells, and tissues) as exploitable resources, high-throughput technologies as tools, and "Big Data" as currency. Prediagnostics and genomics-based analyses successfully entered the public domain more or less unfiltered, offering numerous business opportunities envisioning individuals to contribute to the health sector by providing biomaterial and data as well as by using technology, thus becoming participants and informed coproducers of health. Exploring strengths and weaknesses, as well as opportunities and threats by S.W.O.T. analysis, we highlight some chances, pitfalls, and biases of this sector from a bioscience ethics stance. We conclude that the shift from diagnostic to predictive interpretation of data that comes along with integrative biology seems to escape the general and sometimes the experts' awareness. Moreover, rapid translation into products for the global health market is based on marketable views on health and disease that in turn affect basic research through, for example, funding policies and the research questions being asked. Along with this, biological reductionism is revived fuelling simplified understandings of the genotype phenotype relationship in terms of biology and the human dimension in a broader sense, as well as visions of achieving human perfection through novel biotechnologies.

Quantitative Operating Principles of Yeast Metabolism during Adaptation to Heat Stress

Microorganisms evolved adaptive responses to survive stressful challenges in ever-changing environments. Understanding the relationships between the physiological/metabolic adjustments allowing cellular stress adaptation and gene expression changes being used by organisms to achieve such adjustments may significantly impact our ability to understand and/or guide evolution. Here, we studied those relationships during adaptation to various stress challenges in Saccharomyces cerevisiae, focusing on heat stress responses. We combined dozens of independent experiments measuring whole-genome gene expression changes during stress responses with a simplified kinetic model of central metabolism. We identified alternative quantitative ranges for a set of physiological variables in the model (production of ATP, trehalose, NADH, etc.) that are specific for adaptation to either heat stress or desiccation/rehydration. Our approach is scalable to other adaptive responses and could assist in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes.

The Gene-Centric Content Management System and Its Application for Cognitive Proteomics

The Human Proteome Project is moving into the next phase of creating and/or reconsidering the functional annotations of proteins using the chromosome-centric paradigm. This challenge cannot be solved exclusively using automated means, but rather requires human intelligence for interpreting the combined data. To foster the integration between human cognition and post-genome array a number of specific tools were recently developed, among them CAPER, GenomewidePDB, and The Proteome Browser (TPB). For the purpose of tackling the task of protein functional annotating the Gene-Centric Content Management System (GenoCMS) was expanded with new features. The goal was to enable bioinformaticans to develop self-made applications and to position these applets within the generalized informational canvas supported by GenoCMS. We report the results of GenoCMS-enabled integration of the concordant informational flows in the chromosome-centric framework of the human chromosome 18 project. The workflow described in the article can be scaled to other human chromosomes, and also supplemented with new tracks created by the user. The GenoCMS is an example of a project-oriented informational system, which are important for public data sharing.

Integrating the whole from the sum of the parts: vignettes in computational biology

As is typical of contemporary cutting-edge interdisciplinary fields, computational biology touches and impacts many disciplines ranging from fundamental studies in the areas of genomics, proteomics transcriptomics, lipidomics to practical applications such as personalized medicine, drug discovery, and synthetic biology. This editorial examines the multifaceted role computational biology plays. Using the tools of deep learning, it can make powerful predictions of many biological variables, which may not provide a deep understanding of what factors contribute to the phenomena. Alternatively, it can provide the how and the why of biological processes. Most importantly, it can help guide and interpret what experiments and biological systems to study.

Preventing Electromagnetic Pulse Irradiation Damage on Testis Using Selenium-rich Cordyceps Fungi. A Preclinical Study in Young Male Mice

Networked 21st century society, globalization, and communications technologies are paralleled by the rise of electromagnetic energy intensity in our environments and the growing pressure of the environtome on human biology and health. The latter is the entire complement of environmental factors, including the electromagnetic energy and the technologies that generate them, enacting on the digital citizen in the new century. Electromagnetic pulse (EMP) irradiation might have serious damaging effects not only on electronic equipment but also in the whole organism and reproductive health, through nonthermal effects and oxidative stress. We sought to determine whether EMP exposure (1) induces biological damage on reproductive health and (2) the extent to which selenium-rich Cordyceps fungi (daily coadministration) offer protection on the testicles and spermatozoa. In a preclinical randomized study, 3-week-old male BALB/c mice were repeatedly exposed to EMP (peak intensity 200 kV/m, pulse edge 3.5 ns, pulse width 15 ns, 0.1 Hz, and 400 pulses/day) 5 days per week for four consecutive weeks, with or without coadministration of daily selenium-rich Cordyceps fungi (100 mg/kg). Testicular index and spermatozoa formation were measured at baseline and 1, 7, 14, 28, and 60 day time points after EMP exposure. The group without Cordyceps cotreatment displayed decreased spermatozoa formation, shrunk seminiferous tubule diameters, and diminished antioxidative capacity at 28 and 60 days after exposure (p < 0.05). The Cordyceps daily cotreatment alleviated the testicular damage by EMP exposure, increased spermatozoa formation, and reduced apoptotic spermatogenic cells. These observations warrant further preclinical and clinical studies as an innovative approach for potential protection against electromagnetic radiation in the current age of networked society and digital citizenship.

Biomarkers in Tumor Microenvironment? Upregulation of Fibroblast Activation Protein-α Correlates with Gastric Cancer Progression and Poor Prognosis

Gastric cancer is the third leading cause of cancer-related mortality worldwide. Recent evidence points to importance of cross talk between cancer cells and the surrounding stroma on gastric cancer progression. Tumor microenvironment biomarkers thus represent a new opportunity for diagnostics innovation. Reactive stromal fibroblasts selectively express the fibroblast activation protein alpha (FAP-α), a homodimeric integral membrane gelatinase that belongs to the serine protease family. We report here that FAP-α expression is significantly elevated in gastric cancer samples by more than fivefold (p < 0.05), using transcriptome data from The Cancer Genome Atlas. Notably, the greatest FAP-α upregulation was observed in the poorly differentiated group (p < 0.001). Moreover, elevated FAP-α expression levels correlated with adverse clinical-pathological characteristics, such as diffuse histological subtype (p < 0.001), advanced pathological stage (p < 0.01) and poor survival. Functional annotation analysis demonstrated that FAP-α upregulation was associated with activation of biological processes implicated in tumor progression, including cell migration and angiogenesis pathways. These observations underscore the possible prognostic significance of FAP-α in gastric cancer and its potential as a novel biomarker for personalized medicine. We caution, however, that further multiomics, biochemical, and animal studies are necessary to ascertain the role of FAP-α as a causative and mechanistic biomarker. Based on pathway analyses, we hypothesize that gastric cancer patients exhibiting FAP-α upregulation might presumably benefit from antiangiogenic drugs in addition to standard therapeutic regimens. We call for future research focusing on the tumor microenvironment biomarkers in clinical oncology.

Protein-Protein Interactions in Virus-Host Systems

To study virus–host protein interactions, knowledge about viral and host protein architectures and repertoires, their particular evolutionary mechanisms, and information on relevant sources of biological data is essential. The purpose of this review article is to provide a thorough overview about these aspects. Protein domains are basic units defining protein interactions, and the uniqueness of viral domain repertoires, their mode of evolution, and their roles during viral infection make viruses interesting models of study. Mutations at protein interfaces can reduce or increase their binding affinities by changing protein electrostatics and structural properties. During the course of a viral infection, both pathogen and cellular proteins are constantly competing for binding partners. Endogenous interfaces mediating intraspecific interactions—viral–viral or host–host interactions—are constantly targeted and inhibited by exogenous interfaces mediating viral–host interactions. From a biomedical perspective, blocking such interactions is the main mechanism underlying antiviral therapies. Some proteins are able to bind multiple partners, and their modes of interaction define how fast these “hub proteins” evolve. “Party hubs” have multiple interfaces; they establish simultaneous/stable (domain–domain) interactions, and tend to evolve slowly. On the other hand, “date hubs” have few interfaces; they establish transient/weak (domain–motif) interactions by means of short linear peptides (15 or fewer residues), and can evolve faster. Viral infections are mediated by several protein–protein interactions (PPIs), which can be represented as networks (protein interaction networks, PINs), with proteins being depicted as nodes, and their interactions as edges. It has been suggested that viral proteins tend to establish interactions with more central and highly connected host proteins. In an evolutionary arms race, viral and host proteins are constantly changing their interface residues, either to evade or to optimize their binding capabilities. Apart from gaining and losing interactions via rewiring mechanisms, virus–host PINs also evolve via gene duplication (paralogy); conservation (orthology); horizontal gene transfer (HGT) (xenology); and molecular mimicry (convergence). The last sections of this review focus on PPI experimental approaches and their limitations, and provide an overview of sources of biomolecular data for studying virus–host protein interactions.

A New Tessera into the Interactome of the isc Operon: A Novel Interaction between HscB and IscS

Iron sulfur clusters are essential universal prosthetic groups which can be formed inorganically but, in biology, are bound to proteins and produced enzymatically. Most of the components of the machine that produces the clusters are conserved throughout evolution. In bacteria, they are encoded in the isc operon. Previous reports provide information on the role of specific components but a clear picture of how the whole machine works is still missing. We have carried out a study of the effects of the co-chaperone HscB from the model system E. coli. We document a previously undetected weak interaction between the chaperone HscB and the desulfurase IscS, one of the two main players of the machine. The binding site involves a region of HscB in the longer stem of the approximately L-shaped molecule, whereas the interacting surface of IscS overlaps with the surface previously involved in binding other proteins, such as ferredoxin and frataxin. Our findings provide an entirely new perspective to our comprehension of the role of HscB and propose this protein as a component of the IscS complex.

Using an integrative approach to investigate the evolution of behaviour

Behaviour is a central focus of interest in biology because it has an impact on several aspects of an organism's life. Evolutionary biologists have realised the advantage of an integrative approach that jointly studies the molecular, cellular and physiological levels of an individual to link them with the organismal behavioural phenotype. First, this mechanistic information helps in understanding physiological and evolutionary constraints acting on the behavioural response to the environment and its evolution. Second, it furthers our understanding of the process of molecular convergent evolution. Finally, we learn about natural variation in molecular, cellular and physiological traits present in wild populations and their underlying genetic basis, which can be a substrate for selection to act on. I illustrate these points using our work on behaviour variation in fishes. The information on the mechanistic bases of behaviour variation in various species and behaviours will contribute to an ecological annotation of genes and to uncover new mechanisms implicated in how this astonishing behavioural diversity arose, is maintained and will evolve.

CGAT: a model for immersive personalized training in computational genomics

How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics.

Thermodynamical journey in plant biology

Nonequilibrium irreversible thermodynamics constitute a meaningful point of view suitable to explore life with a rich paradigm. This analytical framework can be used to span the gap from molecular processes to plant function and shows great promise to create a holistic description of life. Since living organisms dissipate energy, exchange entropy and matter with their environment, they can be assimilated to dissipative structures. This concept inherited from nonequilibrium thermodynamics has four properties which defines a scale independent framework suitable to provide a simpler and more comprehensive view of the highly complex plant biology. According to this approach, a biological function is modeled as a cascade of dissipative structures. Each dissipative structure, corresponds to a biological process, which is initiated by the amplification of a fluctuation. Evolution of the process leads to the breakage of the system symmetry and to the export of entropy. Exporting entropy to the surrounding environment corresponds to collecting information about it. Biological actors which break the symmetry of the system and which store information are by consequence, key actors on which experiments and data analysis focus most. This paper aims at illustrating properties of dissipative structure through familiar examples and thus initiating the dialogue between nonequilibrium thermodynamics and plant biology.

Chemotherapy and signaling: How can targeted therapies supercharge cytotoxic agents?

In recent years, oncologists have begun to conclude that chemotherapy has reached a plateau of efficacy as a primary treatment modality, even if toxicity can be effectively controlled. Emerging specific inhibitors of signaling and metabolic pathways (i.e., targeted agents) contrast with traditional chemotherapy drugs in that the latter primarily interfere with the DNA biosynthesis and the cell replication machinery. In an attempt to improve on the efficacy, combination of targeted drugs with conventional chemotherapeutics has become a routine way of testing multiple new agents in early phase clinical trials. This review discusses the recent advances including integrative systematic biology and RNAi approaches to counteract the chemotherapy resistance and to buttress the selectivity, efficacy and personalization of anti-cancer drug therapy.

A combined computational-experimental analyses of selected metabolic enzymes in Pseudomonas species

Comparative genomic analysis has revolutionized our ability to predict the metabolic subsystems that occur in newly sequenced genomes, and to explore the functional roles of the set of genes within each subsystem. These computational predictions can considerably reduce the volume of experimental studies required to assess basic metabolic properties of multiple bacterial species. However, experimental validations are still required to resolve the apparent inconsistencies in the predictions by multiple resources. Here, we present combined computational-experimental analyses on eight completely sequenced Pseudomonas species. Comparative pathway analyses reveal that several pathways within the Pseudomonas species show high plasticity and versatility. Potential bypasses in 11 metabolic pathways were identified. We further confirmed the presence of the enzyme O-acetyl homoserine (thiol) lyase (EC: 2.5.1.49) in P. syringae pv. tomato that revealed inconsistent annotations in KEGG and in the recently published SYSTOMONAS database. These analyses connect and integrate systematic data generation, computational data interpretation, and experimental validation and represent a synergistic and powerful means for conducting biological research.

Spherophylon, the concept of life at a level higher than that of the individual

A new term, spherophylon, indicates a unit of life higher than the individual level. To define this term, critical notes are given on the meaning of age in terms of life, the interrelationships among the elements of biodiversity, and an analogy of development between the multicellular body of an individual and the spherophylon. Life is compared at various levels; at the level of the cell, the individual as a multicellular organism, and the spherophylon. The biology of the spherophylon is discussed in the context of integrative biology.