Biological Questions Research Articles

Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.

Understanding cell state transitions and their governing regulatory mechanisms remains one of the fundamental questions in biology. We develop a computational method, state transition inference using cross-cell correlations (STICCC), for predicting reversible and irreversible cell state transitions at single-cell resolution by using gene expression data and a set of gene regulatory interactions. The method is inspired by the fact that the gene expression time delays between regulators and targets can be exploited to infer past and future gene expression states. From applications to both simulated and experimental single-cell gene expression data, we show that STICCC-inferred vector fields capture basins of attraction and irreversible fluxes. By connecting regulatory information with systems' dynamical behaviors, STICCC reveals how network interactions influence reversible and irreversible state transitions. Compared to existing methods that infer pseudotime and RNA velocity, STICCC provides complementary insights into the gene regulation of cell state transitions.

Off the beaten track: Understudied microbes and their potential

The world of microbes is diverse, but the majority of these fascinating organisms are not as famous (or perhaps infamous) as their pathogenic counterparts. Cell highlights six scientists whose work addresses some of the most fundamental questions in biology, even though their microbial models may seem a tad bit unconventional.

Ecological, genetic and geographical divergence explain differences in colouration among sunbird species (Nectariniidae).

How extravagant ornamental traits evolve is a key question in evolutionary biology. Bird plumages are among the most elaborate ornaments, displaying almost all colours of the rainbow. Why and how birds evolved to be so colourful remains an open question with multiple and sometimes competing hypotheses. Different colours in different patches (i.e. body parts) might have different functions and thus result from different forms of selection (e.g. natural vs. sexual selection). Here we test the influence of three factors on colour diversity in sunbirds: (1) geographical distance, (2) differences in light environment and (3) phylogenetic distances. We show that both natural and sexual selection affect the evolution of sunbird colouration, but that their extent and direction differs between sexes, and varies with the extent of species overlap and across different patches on the body. Even though overlap in light environment partially explains colour differences among species, no colour metric (brightness, hue or chroma) covaries with light environment. Our results suggest that multiple forms of selection influence the colouration of different colour patches in different ways across an organism's body, highlighting the need to investigate colouration as a network of individual but inter-connected colour patches. These results are likely to be generalizable across the multitude of colourful animals.

Live Cell Painting: image-based profiling in live cells using Acridine Orange.

Image-based profiling has been used to analyze cell health, drug mechanism of action, CRISPR-edited cells, and overall cytotoxicity. Cell Painting is a broadly used image-based assay that uses morphological features to capture how cells respond to treatments. However, this method requires cell fixation for staining, which prevents examining live cells. To address this limitation, here we present Live Cell Painting (LCP), a high-content method based on Acridine orange, a metachromatic dye that labels different organelles and cellular structures. We began by showing that LCP can be applied to follow acidic vesicle redistribution of cells exposed to acidic vesicles inhibitors. Next, we show that LCP can identify subtle changes in cells exposed to silver nanoparticles that are not detected by techniques such as MTT assay. In drug treatments, LCP was helpful in assessing the dose-response relationship and creating profiles that allow clustering of drugs that cause liver injury. Here, we present an affordable and easy-to-use image-based assay capable of assessing overall cell health and showing promise for use in various applications such as assessing drugs and nanoparticles. We envisage the use of Live Cell Painting as an initial screening of overall cell health while providing insights into new biological questions.

Fungal elemental profiling unleashed through rapid laser-induced breakdown spectroscopy (LIBS).

Historically, ionomics, the elemental profiling of an organism or materials, has been used to understand the elemental composition in waste materials to identify and recycle heavy metals or rare earth elements, identify the soil composition in space exploration on the moon or Mars, or understand human disorders or disease. To our knowledge, ionomic profiling of microbes, particularly fungi, has not been investigated to answer applied and fundamental biological questions. The reason is that current ionomic analytical techniques can be laborious in sample preparation, fail to measure all potential elements accurately, are cost-prohibitive, or provide inconsistent results across replications. In our previous efforts, we explored whether laser-induced breakdown spectroscopy (LIBS) could be used in determining the elemental profiles of poplar tissue, which was successful. In this proof-of-concept endeavor, we undertook a transdisciplinary effort between applied and fundamental mycology and elemental analytical techniques to address the biological question of how LIBS can used for fungi grown axenically in a nutrient-rich and nutrient-poor environment.

MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis

BackgroundWhile sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack sufficient tools and methods that allow for an in-depth analysis of sex as a variable in biomedical research. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness.DescriptionMetaFun is a complete suite that allows the analysis of transcriptomics data and the exploration of the results at all levels, performing single-dataset exploratory analysis, differential gene expression, gene set functional enrichment, and finally, combining results in a functional meta-analysis. Which biological processes, molecular functions or cellular components are altered in a common pattern in different transcriptomic studies when comparing male and female patients? This and other biological questions of interest can be answered with the use of MetaFun. This tool is available at https://bioinfo.cipf.es/metafun while additional help can be found at https://gitlab.com/ubb-cipf/metafunweb/-/wikis/Summary.ConclusionsOverall, Metafun is the first open-access web-based tool to identify consensus biological functions across multiple transcriptomic datasets, helping to elucidate sex differences in numerous diseases. Its use will facilitate the generation of novel biological knowledge that can be used in the research and application of Personalized Medicine considering the sex of patients.

An integrative understanding of evolutionary convergence across organisms and biological scales.

The extent to which evolution is predictable is a long-standing question in biology, with implications for urgent biological issues such as viral evolution, the emergence of antibiotic resistance in bacteria, and organismal responses to climate change. Convergent evolution, the phylogenetically independent evolution of similar phenotypes, provides biological replicates useful for exploring patterns of predictability in evolution. Understanding evolutionary convergence requires synthesizing findings across biological scales and organisms. To this end, we organized a SICB-wide symposium entitled "Integrating research on convergent evolution across levels of biological organization, organisms, and time". Our symposium showcased interdisciplinary research on evolutionary convergence across diverse study systems and levels of biological organization, while highlighting new techniques and comparative methods for identifying patterns of predictability in convergently evolved traits. Here, we introduce findings from papers included in this symposium issue and identify common themes, highlight emerging questions, and discuss how we can integrate new techniques, tools, and systems to expand our understanding of evolutionary convergence.

PIPETS: A statistically informed, gene-annotation agnostic analysis method to study bacterial termination using 3'-end sequencing.

Over the last decade the drop in short-read sequencing costs have allowed experimental techniques utilizing sequencing to address specific biological questions to proliferate, oftentimes outpacing standardized or effective analysis approaches for the data generated. There are growing amounts of bacterial 3'-end sequencing data, yet there is currently no commonly accepted analysis methodology for this datatype. Most data analysis approaches are somewhat ad hoc and, despite the presence of substantial signal within annotated genes, focus on genomic regions outside the annotated genes (e.g. 3' or 5' UTRs). Furthermore, lack of a systematic approach to analyzing such data makes it impossible to compare conclusions generated by different labs, using different organisms. We present PIPETS ( P oisson I dentification of PE aks from T erm- S eq data), an R package available on Bioconductor that provides a novel analysis method for 3'-end sequencing data. PIPETS is a statistically informed, gene-annotation agnostic methodology. Across two different datasets PIPETS identified significant 3'-end termination signal across a wider range of annotated genomic contexts than existing analysis approaches, suggesting that existing approaches may miss biologically relevant signal. Furthermore, assessment of the previously called 3'-end positions not captured by PIPETS showed that they were uniformly very low coverage. PIPETS provides a broadly applicable platform to compare 3'-end sequencing data sets across different organisms. It requires only the 3'-end sequencing data, and is broadly accessible to non-expert users.

Mating systems and recombination landscape strongly shape genetic diversity and selection in wheat relatives

Abstract How and why genetic diversity varies among species is a long-standing question in evolutionary biology. Life history traits have been shown to explain a large part of observed diversity. Among them, mating systems have one of the strongest impacts on genetic diversity, with selfing species usually exhibiting much lower diversity than outcrossing relatives. Theory predicts that a high rate of selfing amplifies selection at linked sites, reducing genetic diversity genome-wide, but frequent bottlenecks and rapid population turn-over could also explain low genetic diversity in selfers. However, how linked selection varies with mating systems and whether it is sufficient to explain the observed difference between selfers and outcrossers has never been tested. Here, we used the Aegilops/Triticum grass species, a group characterized by contrasted mating systems (from obligate outcrossing to high selfing) and marked recombination rate variation across the genome, to quantify the effects of mating system and linked selection on patterns of neutral and selected polymorphism. By analyzing phenotypic and transcriptomic data of 13 species, we show that selfing strongly affects genetic diversity and the efficacy of selection by amplifying the intensity of linked selection genome-wide. In particular, signatures of adaptation were only found in the highly recombining regions in outcrossing species. These results bear implications for the evolution of mating systems and, more generally, for our understanding of the fundamental drivers of genetic diversity.

A Chimeric ORF Fusion Phenotypic Reporter for Cryptococcus neoformans.

The plethora of genome sequences produced in the postgenomic age has not resolved many of our most pressing biological questions. Correlating gene expression with an interrogatable and easily observable characteristic such as the surrogate phenotype conferred by a reporter gene is a valuable approach to gaining insight into gene function. Many reporters including lacZ, amdS, and the fluorescent proteins mRuby3 and mNeonGreen have been used across all manners of organisms. Described here is an investigation into the creation of a robust, synthetic, fusion reporter system for Cryptococcus neoformans that combines some of the most useful fluorophores available in this system with the versatility of the counter-selectable nature of amdS. The reporters generated include multiple composition and orientation variants, all of which were investigated for differences in expression. Evaluation of known promoters from the TEF1 and GAL7 genes was undertaken, elucidating novel expression tendencies of these biologically relevant C. neoformans regulators of transcription. Smaller than lacZ but providing multiple useful surrogate phenotypes for interrogation, the fusion ORF serves as a superior whole-cell assay compared to traditional systems. Ultimately, the work described here bolsters the array of relevant genetic tools that may be employed in furthering manipulation and understanding of the WHO fungal priority group pathogen C. neoformans.

Implementing distinct spatial proteogenomic technologies: opportunities, challenges, and key considerations.

Our ability to understand the cellular complexity of tissues has been revolutionized in recent years with significant advances in proteogenomic technologies including those enabling spatial analyses. This has led to numerous consortium efforts, such as the human cell atlas initiative which aims to profile all cells in the human body in healthy and diseased contexts. The availability of such information will subsequently lead to the identification of novel biomarkers of disease and of course therapeutic avenues. However, before such an atlas of any given healthy or diseased tissue can be generated, several factors should be considered including which specific techniques are optimal for the biological question at hand. In this review, we aim to highlight some of the considerations we believe to be important in the experimental design and analysis process, with the goal of helping to navigate the rapidly changing landscape of technologies available.

Active shape programming drives Drosophila wing disc eversion.

How complex 3D tissue shape emerges during animal development remains an important open question in biology and biophysics. Here, we discover a mechanism for 3D epithelial shape change based on active, in-plane cellular events that is analogous to inanimate "shape programmable" materials, which undergo blueprinted 3D shape transformations from in-plane gradients of spontaneous strains. We study eversion of the Drosophila wing disc pouch, when the epithelium transforms from a dome into a curved fold, quantifying 3D tissue shape changes and mapping spatial patterns of cellular behaviors on the evolving geometry using cellular topology. Using a physical model inspired by shape programming, we find that active cell rearrangements are the major contributor to pouch eversion and validate this conclusion using a knockdown of MyoVI, which reduces rearrangements and disrupts morphogenesis. This work shows that shape programming is a mechanism for animal tissue morphogenesis and suggests that patterns in nature could present design strategies for shape-programmable materials.

TOMOMAN: a software package for large scale cryo-electron tomography data preprocessing, community data sharing, and collaborative computing.

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) are becoming the preferred methodologies for investigating subcellular and macromolecular structures in native or near-native environments. While cryo-ET is amenable to a wide range of biological problems, these problems often have data processing requirements that need to be individually optimized, precluding the notion of a one-size-fits-all processing pipeline. Cryo-ET data processing is also becoming progressively more complex due to an increasing number of packages for each processing step. Though each package has its own strengths and weaknesses, independent development and different data formats makes them difficult to interface with one another. TOMOMAN (TOMOgram MANager) is an extensible package for streamlining the interoperability of packages, enabling users to develop project-specific processing workflows. TOMOMAN does this by maintaining an internal metadata format and wrapping external packages to manage and perform preprocessing, from raw tilt-series data to reconstructed tomograms. TOMOMAN can also export this metadata between various STA packages. TOMOMAN also includes tools for archiving projects to data repositories; allowing subsequent users to download TOMOMAN projects and directly resume processing where it was previously left off. By tracking essential metadata, TOMOMAN streamlines data sharing, which improves reproducibility of published results, reduces computational costs by minimizing reprocessing, and enables distributed cryo-ET projects between multiple groups and institutions. TOMOMAN provides a way for users to test different software packages to develop processing workflows that meet the specific needs of their biological questions and to distribute their results with the broader scientific community.

A Guided Tour of Phylogenetic Comparative Methods for Studying Trait Evolution

Phylogenetic comparative methods are important tools in biology, providing insights into the way traits evolve. There are many technical resources describing how these methods work. Our aim here is to complement these with an overview of the types of biological questions that can be addressed by different methods and to outline potential pitfalls and considerations when embarking on comparative studies. First, we introduce what comparative methods are and why they are important. Second, we outline how they can be used to understand when, where, and how frequently traits evolve. Third, we examine how the coevolution of traits within and between species can be studied, along with patterns of causality. Finally, we discuss how to approach comparative analyses and the ways in which different types of data, such as published relationships, omic, and remote sensing data, can be integrated.

Open-source, high-throughput targeted in situ transcriptomics for developmental and tissue biology.

Multiplexed spatial profiling of mRNAs has recently gained traction as a tool to explore the cellular diversity and the architecture of tissues. We propose a sensitive, open-source, simple and flexible method for the generation of in situ expression maps of hundreds of genes. We use direct ligation of padlock probes on mRNAs, coupled with rolling circle amplification and hybridization-based in situ combinatorial barcoding, to achieve high detection efficiency, high-throughput and large multiplexing. We validate the method across a number of species and show its use in combination with orthogonal methods such as antibody staining, highlighting its potential value for developmental and tissue biology studies. Finally, we provide an end-to-end computational workflow that covers the steps of probe design, image processing, data extraction, cell segmentation, clustering and annotation of cell types. By enabling easier access to high-throughput spatially resolved transcriptomics, we hope to encourage a diversity of applications and the exploration of a wide range of biological questions.

Physical modeling of embryonic transcriptomes identifies collective modes of gene expression.

Starting from one totipotent cell, complex multicellular organisms form through a series of differentiation and morphogenetic events, culminating in a multitude of cell types arranged in a functional and intricate spatial pattern. To do so, cells coordinate with each other, resulting in dynamics which follow a precise developmental trajectory, constraining the space of possible embryo-to-embryo variation. Using recent single-cell sequencing data of early ascidian embryos, we leverage natural variation together with modeling and inference techniques from statistical physics to investigate development at the level of a complete interconnected embryo - an embryonic transcriptome. After developing a robust and biophysically motivated approach to identifying distinct transcriptomic states or cell types, a statistical analysis reveals correlations within embryos and across cell types demonstrating the presence of collective variation. From these intra-embryo correlations, we infer minimal networks of cell-cell interactions, which reveal the collective modes of gene expression. Our work demonstrates how the existence and nature of spatial interactions along with the collective modes of expression that they give rise to can be inferred from single-cell gene expression measurements, opening up a wider range of biological questions that can be addressed using sequencing-based modalities.

Optogenetic control of phosphate-responsive genes using single component fusion proteins in Saccharomyces cerevisiae.

Blue light illumination can be detected by Light-Oxygen-Voltage (LOV) photosensing proteins and translated into a range of biochemical responses, facilitating the generation of novel optogenetic tools to control cellular function. Here we develop new variants of our previously described VP-EL222 light-dependent transcription factor and apply them to study the phosphate-responsive signaling (PHO) pathway in the budding yeast Saccharomyces cerevisiae, exemplifying the utilities of these new tools. Focusing first on the VP-EL222 protein itself, we quantified the tunability of gene expression as a function of light intensity and duration, and demonstrated that this system can tolerate the addition of substantially larger effector domains without impacting function. We further demonstrated the utility of several EL222-driven transcriptional controllers in both plasmid and genomic settings, using the PHO5 and PHO84 promoters in their native chromosomal contexts as examples. These studies highlight the utility of light-controlled gene activation using EL222 tethered to either artificial transcription domains or yeast activator proteins (Pho4). Similarly, we demonstrate the ability to optogenetically repress gene expression with EL222 fused to the yeast Ume6 protein. We finally investigated the effects of moving EL222 recruitment sites to different locations within the PHO5 and PHO84 promoters, as well as determining how this artificial light-controlled regulation could be integrated with the native controls dependent on inorganic phosphate (Pi) availability. Taken together, our work expands the applicability of these versatile optogenetic tools in the types of functionality they can deliver and biological questions that can be probed.

Convergent evolution of plant prickles by repeated gene co-option over deep time.

An enduring question in evolutionary biology concerns the degree to which episodes of convergent trait evolution depend on the same genetic programs, particularly over long timescales. In this work, we genetically dissected repeated origins and losses of prickles-sharp epidermal projections-that convergently evolved in numerous plant lineages. Mutations in a cytokinin hormone biosynthetic gene caused at least 16 independent losses of prickles in eggplants and wild relatives in the genus Solanum. Homologs underlie prickle formation across angiosperms that collectively diverged more than 150 million years ago, including rice and roses. By developing new Solanum genetic systems, we leveraged this discovery to eliminate prickles in a wild species and an indigenously foraged berry. Our findings implicate a shared hormone activation genetic program underlying evolutionarily widespread and recurrent instances of plant morphological innovation.

α-Mannosylated HLA-II glycopeptide antigens dominate the immunopeptidome of immortalised cells and tumour tissues.

Immunopeptides are cell surface-located protein fragments that aid our immune system to recognise and respond to pathogenic insult and malignant transformation. In this two-part communication, we firstly summarise and reflect on our recent discovery documenting that MHC-II-bound immunopeptides from immortalised cell lines prevalently carry N-glycans that differ from the cellular glycoproteome (Goodson, Front Immunol, 2023). These findings are important as immunopeptide glycosylation remains poorly understood in immunosurveillance. The study also opened up new technical and biological questions that we address in the second part of this communication. Our study highlighted that the performance of the search engines used to detect glycosylated immunopeptides from LC-MS/MS data remains untested and, importantly, that little biochemical in vivo evidence is available to document the nature of glycopeptide antigens in tumour tissues. To this end, we compared the N-glycosylated MHC-II-bound immunopeptides that were reported from tumour tissues of 14 meningioma patients in the MSFragger-HLA-Glyco database (Bedran, Nat Commun, 2023) to those we identified with the commercial Byonic software. Encouragingly, the search engines produced similar outputs supporting that N-glycosylated MHC-II-bound immunopeptides are prevalent in meningioma tumour tissues. Consistent also with in vitro findings, the tissue-derived MHC-II-bound immunopeptides were found to predominantly carry hyper-processed (paucimannosidic- and chitobiose core-type) and hypo-processed (oligomannosidic-type) N-glycans that varied in prevalence and distribution between patients. Taken together, evidence is emerging suggesting that α-mannosidic glycoepitopes abundantly decorate MHC-II-bound immunopeptides presented in both immortalised cells and tumour tissues warranting further research into their functional roles in immunosurveillance.

Proterozoic microfossils continue to provide new insights into the rise of complex eukaryotic life.

Eukaryotes have evolved to dominate the biosphere today, accounting for most documented living species and the vast majority of the Earth's biomass. Consequently, understanding how these biologically complex organisms initially diversified in the Proterozoic Eon over 539 million years ago is a foundational question in evolutionary biology. Over the last 70 years, palaeontologists have sought to document the rise of eukaryotes with fossil evidence. However, the delicate and microscopic nature of their sub-cellular features affords early eukaryotes diminished preservation potential. Chemical biomarker signatures of eukaryotes and the genetics of living eukaryotes have emerged as complementary tools for reconstructing eukaryote ancestry. In this review, we argue that exceptionally preserved Proterozoic microfossils are critical to interpreting these complementary tools, providing crucial calibrations to molecular clocks and testing hypotheses of palaeoecology. We highlight recent research on their preservation and biomolecular composition that offers new ways to enhance their utility.