Is central dogma a global property of cellular information flow?

Towards multi-omics synthetic data integration

Across many scientific disciplines, the development of computational models and algorithms for generating artificial or synthetic data is gaining momentum. In biology, there is a great opportunity to explore this further as more and more big data at multi-omics level are generated recently. In this opinion, we discuss the latest trends in biological applications based on process-driven and data-driven aspects. Moving ahead, we believe these methodologies can help shape novel multi-omics-scale cellular inferences.

Glycobiology of Cancer: Sugar Drives the Show

Cancer development and progression is associated with aberrant changes in cellular glycosylation. Cells expressing altered glycan-structures are recognized by cells of the immune system, favoring the induction of inhibitory immune processes which subsequently promote tumor growth and spreading. Here, we discuss about the importance of glycobiology in modern medicine, taking into account the impact of altered glycan structures expressed in cancer cells as potential glycobiomarkers of disease, as well as on cancer development and progression.

Statistical Atlases and Automatic Labeling Strategies to Accelerate the Analysis of Social Insect Brain Evolution

Current methods used to quantify brain size and compartmental scaling relationships in studies of social insect brain evolution involve manual annotations of images from histological samples, confocal microscopy or other sources. This process is susceptible to human bias and error and requires time-consuming effort by expert annotators. Standardized brain atlases, constructed through 3D registration and automatic segmentation, surmount these issues while increasing throughput to robustly sample diverse morphological and behavioral phenotypes. Here we design and evaluate three strategies to construct statistical brain atlases, or templates, using ants as a model taxon. The first technique creates a template by registering multiple brains of the same species. Brain regions are manually annotated on the template, and the labels are transformed back to each individual brain to obtain an automatic annotation, or to any other brain aligned with the template. The second strategy also creates a template from multiple brain images but obtains labels as a consensus from multiple manual annotations of individual brains comprising the template. The third technique is based on a template comprising brains from multiple species and the consensus of their labels. We used volume similarity as a metric to evaluate the automatic segmentation produced by each method against the inter- and intra-individual variability of human expert annotators. We found that automatic and manual methods are equivalent in volume accuracy, making the template technique an extraordinary tool to accelerate data collection and reduce human bias in the study of the evolutionary neurobiology of ants and other insects.

Identifying toggle genes from transcriptome-wide scatter: A new perspective for biological regulation

The study of gene expression variability, especially for cancer and cell differentiation studies, has become important. Here, we investigate transcriptome-wide scatter of 23 cell types and conditions across different levels of biological complexity. We focused on genes that act like toggle switches between pairwise replicates of the same cell type, i.e. genes expressed in one replicate and not expressed in the other, sometimes also referred as ON/OFF genes. The proportion of these toggle genes dramatically increases from unicellular to multicellular organization, especially for development and cancer cells. A relevant portion of toggle switches are non-coding genes: in unicellular systems the most represented classes are tRNA and rRNA, while multicellular systems more frequently show lncRNA, sncRNA and pseudogenes. Notably, disease associated microRNAs (miRNAs), pseudogenes and numerous uncharacterized transcripts are present in both development and cancer cells. On top of the known intrinsic and extrinsic factors, our work indicates toggle genes as a novel collective component creating transcriptome-wide variability. This requires further investigation for elucidating both evolutionary and disease processes.

Olfactory System Morphology Suggests Colony Size Drives Trait Evolution in Odorous Ants (Formicidae: Dolichoderinae)

In social insects colony fitness is determined in part by individual worker phenotypes. Across ant species, colony size varies greatly and is thought to affect worker trait variation in both proximate and ultimate ways. Little is known about the relationship between colony size and worker trait evolution, but hypotheses addressing the role of social structure in brain evolution suggest workers of small-colony species may have larger brains or larger brain regions necessary for complex behaviors. In previous work on odorous ants (Formicidae: Dolichoderinae) we found no correlation between colony size and these brain properties, but found that relative antennal lobe size scaled negatively with colony size. Therefore, we now test whether sensory systems scale with colony size, with particular attention to olfactory components thought to be involved in nestmate recognition. Across three species of odorous ants, Forelius mccooki, Dorymyrmex insanus, and D. bicolor, which overlap in habitat and foraging ecology but vary in colony size, we compare olfactory sensory structures, comparing those thought to be involved in nestmate recognition. We use the visual system, a sensory modality not as important in social communication in ants, as a control comparison. We find that body size scaling largely explains differences in eye size, antennal length, antennal sensilla density, and total number of olfactory glomeruli across these species. However, sensilla basiconica and olfactory glomeruli in the T6 cluster of the antennal lobe, structures known to be involved in nestmate recognition, do not follow body size scaling observed for other structures. Instead, we find evidence from the closely related Dorymyrmex species that the larger colony species, D. bicolor, invests more in structures implicated in nestmate recognition. To test for functional consequences, we compare nestmate and non-nestmate interactions between these two species and find D. bicolor pairs of either type engage in more interactions than D. insaus pairs. Thus, we do not find evidence supporting a universal pattern of sensory system scaling associated with changes in colony size, but hypothesize that observed differences in the olfactory components in two closely related Dorymyrmex species are evidence of a link between colony size and sensory trait evolution.

The remodel of the "central dogma": a metabolomics interaction perspective

BACKGROUND

In 1957, Francis Crick drew a linear diagram on a blackboard. This diagram is often called the "central dogma." Subsequently, the relationships between different steps of the "central dogma" have been shown to be considerably complex, mostly because of the emerging world of small molecules. It is noteworthy that metabolites can be generated from the diet through gut microbiome metabolism, serve as substrates for epigenetic modifications, destabilize DNA quadruplexes, and follow Lamarckian inheritance. Small molecules were once considered the missing link in the "central dogma"; however, recently they have acquired a central role, and their general perception as downstream products has become reductionist. Metabolomics is a large-scale analysis of metabolites, and this emerging field has been shown to be the closest omics associated with the phenotype and concomitantly, the basis for all omics.

AIM OF REVIEW

Herein, we propose a broad updated perspective for the flux of information diagram centered in metabolomics, including the influence of other factors, such as epigenomics, diet, nutrition, and the gut- microbiome.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Metabolites are the beginning and the end of the flux of information.

Connecting primitive phase separation to biotechnology, synthetic biology, and engineering

One aspect of the study of the origins of life focuses on how primitive chemistries assembled into the first cells on Earth and how these primitive cells evolved into modern cells. Membraneless droplets generated from liquid-liquid phase separation (LLPS) are one potential primitive cell-like compartment; current research in origins of life includes study of the structure, function, and evolution of such systems. However, the goal of primitive LLPS research is not simply curiosity or striving to understand one of life's biggest unanswered questions, but also the possibility to discover functions or structures useful for application in the modern day. Many applicational fields, including biotechnology, synthetic biology, and engineering, utilize similar phaseseparated structures to accomplish specific functions afforded by LLPS. Here, we briefly review LLPS applied to primitive compartment research and then present some examples of LLPS applied to biomolecule purification, drug delivery, artificial cell construction, waste and pollution management, and flavor encapsulation. Due to a significant focus on similar functions and structures, there appears to be much for origins of life researchers to learn from those working on LLPS in applicational fields, and vice versa, and we hope that such researchers can start meaningful cross-disciplinary collaborations in the future.

ScatLay: utilizing transcriptome-wide noise for identifying and visualizing differentially expressed genes

Differential expressed (DE) genes analysis is valuable for understanding comparative transcriptomics between cells, conditions or time evolution. However, the predominant way of identifying DE genes is to use arbitrary threshold fold or expression changes as cutoff. Here, we developed a more objective method, Scatter Overlay or ScatLay, to extract and graphically visualize DE genes across any two samples by utilizing their pair-wise scatter or transcriptome-wide noise, while factoring replicate variabilities. We tested ScatLay for 3 cell types: between time points for Escherichia coli aerobiosis and Saccharomyces cerevisiae hypoxia, and between untreated and Etomoxir treated Mus Musculus embryonic stem cell. As a result, we obtain 1194, 2061 and 2932 DE genes, respectively. Next, we compared these data with two widely used current approaches (DESeq2 and NOISeq) with typical twofold expression changes threshold, and show that ScatLay reveals significantly larger number of DE genes. Hence, our method provides a wider coverage of DE genes, and will likely pave way for finding more novel regulatory genes in future works.

Towards understanding the cell surface phenotype, metabolic properties and immune functions of resident macrophages of the peritoneal cavity and splenic red pulp using high resolution quantitative proteomics

Background:Resident macrophages (Mϕs) are distributed throughout the body and are important for maintaining tissue homeostasis and for defence against infections. Tissue Mϕs are highly adapted to their microenvironment and thought to mediate tissue-specific functions involving metabolism and immune defence that are not fully elucidated. Methods:We have used high resolution quantitative proteomics to gain insights into the functions of two types of resident tissue Mϕs: peritoneal cavity Mϕs and splenic red pulp Mϕs.  The cellular expression levels of many proteins were validated by flow cytometry and were consistently in agreement with the proteomics data.Results:Peritoneal and splenic red pulp macrophages displayed major differences in cell surface phenotype reflecting their adaptation to different tissue microenvironments and tissue-specific functions. Peritoneal Mϕs were shown to be enriched in a number of key enzymes and metabolic pathways normally associated with the liver, such as metabolism of fructose, detoxification, nitrogen homeostasis and the urea cycle. Supporting these observations, we show that peritoneal Mϕs are able to utilise glutamine and glutamate which are rich in peritoneum for urea generation.  In comparison, splenic red pulp Mϕs were enriched in proteins important for adaptive immunity such as antigen presenting MHC molecules, in addition to proteins required for erythrocyte homeostasis and iron turnover. We also show that these tissue Mϕs may utilise carbon and nitrogen substrates for different metabolic fates to support distinct tissue-specific roles.Conclusions:This study provides new insights into the functions of tissue Mϕs in immunity and homeostasis.  The comprehensive proteomics data sets are a valuable resource for biologists and immunologists.

Trends in Symbiont-Induced Host Cellular Differentiation

Bacteria participate in a wide diversity of symbiotic associations with eukaryotic hosts that require precise interactions for bacterial recognition and persistence. Most commonly, host-associated bacteria interfere with host gene expression to modulate the immune response to the infection. However, many of these bacteria also interfere with host cellular differentiation pathways to create a hospitable niche, resulting in the formation of novel cell types, tissues, and organs. In both of these situations, bacterial symbionts must interact with eukaryotic regulatory pathways. Here, we detail what is known about how bacterial symbionts, from pathogens to mutualists, control host cellular differentiation across the central dogma, from epigenetic chromatin modifications, to transcription and mRNA processing, to translation and protein modifications. We identify four main trends from this survey. First, mechanisms for controlling host gene expression appear to evolve from symbionts co-opting cross-talk between host signaling pathways. Second, symbiont regulatory capacity is constrained by the processes that drive reductive genome evolution in host-associated bacteria. Third, the regulatory mechanisms symbionts exhibit correlate with the cost/benefit nature of the association. And, fourth, symbiont mechanisms for interacting with host genetic regulatory elements are not bound by native bacterial capabilities. Using this knowledge, we explore how the ubiquitous intracellular Wolbachia symbiont of arthropods and nematodes may modulate host cellular differentiation to manipulate host reproduction. Our survey of the literature on how infection alters gene expression in Wolbachia and its hosts revealed that, despite their intermediate-sized genomes, different strains appear capable of a wide diversity of regulatory manipulations. Given this and Wolbachia's diversity of phenotypes and eukaryotic-like proteins, we expect that many symbiont-induced host differentiation mechanisms will be discovered in this system.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

Transcriptome-wide variability in single embryonic development cells

Molecular heterogeneity of individual molecules within single cells has been recently shown to be crucial for cell fate diversifications. However, on a global scale, the effect of molecular variability for embryonic developmental stages is largely underexplored. Here, to understand the origins of transcriptome-wide variability of oocytes to blastocysts in human and mouse, we examined RNA-Seq datasets. Evaluating Pearson correlation, Shannon entropy and noise patterns (η²vs.μ), our investigations reveal a phase transition from low to saturating levels of diversity and variability of transcriptome-wide expressions through the development stages. To probe the observed behaviour further, we utilised a stochastic transcriptional model to simulate the global gene expressions pattern for each development stage. From the model, we concur that transcriptome-wide regulation initially begins from 2-cell stage, and becomes strikingly variable from 8-cell stage due to amplification and quantal transcriptional activity.

Endocrinology: advances through omics and related technologies

The rapid development of new omics technologies to measure changes at genetic, transcriptomic, proteomic, and metabolomics levels together with the evolution of methods to analyze and integrate the data at a systems level are revolutionizing the study of biological processes. Here we discuss how new approaches using omics technologies have expanded our knowledge especially in nontraditional models. Our increasing knowledge of these interactions and evolutionary pathway conservation facilitates the use of nontraditional species, both invertebrate and vertebrate, as new model species for biological and endocrinology research. The increasing availability of technology to create organisms overexpressing key genes in endocrine function allows manipulation of complex regulatory networks such as growth hormone (GH) in transgenic fish where disregulation of GH production to produce larger fish has also permitted exploration of the role that GH plays in testis development, suggesting that it does so through interactions with insulin-like growth factors. The availability of omics tools to monitor changes at nearly any level in any organism, manipulate gene expression and behavior, and integrate data across biological levels, provides novel opportunities to explore endocrine function across many species and understand the complex roles that key genes play in different aspects of the endocrine function.