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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Unique genetic variants underlie parallel gene expression within a young adaptive radiation despite specialization on highly divergent resources

Parallel evolution of gene expression commonly underlies convergent niche specialization, but parallel changes in expression could also underlie divergent specialization. We investigated divergence in gene expression and whole-genome genetic variation across three sympatric Cyprinodon pupfishes endemic to San Salvador Island, Bahamas. This recent radiation consists of a generalist and two derived specialists adapted to novel niches - a scale-eater and a snail-eater. We sampled total mRNA from all three species at two early developmental stages and compared gene expression with whole-genome genetic differentiation among all three species in 42 resequenced genomes. 80% of genes that were differentially expressed between snail-eaters and generalists were up or downregulated in the same direction between scale-eaters and generalists; however, there were no fixed variants shared between species underlying these parallel changes in expression. Genes showing parallel evolution of expression were enriched for effects on metabolic processes, whereas genes showing divergent expression were enriched for effects on cranial skeleton development and pigment biosynthesis, reflecting the most divergent phenotypes observed between specialist species. Our findings reveal that even divergent niche specialists may exhibit convergent adaptation to higher trophic levels through shared genetic pathways. This counterintuitive result suggests that parallel evolution in gene expression can accompany divergent ecological speciation during adaptive radiation.\n\nImpact SummaryAdaptations that result in unique forms of ecological specialization are central to research in evolutionary biology, yet little is known about their molecular foundations. We combined transcriptome sequencing with whole-genome divergence scans to study the molecular evolution of two specialist Cyprinodon pupfish species - a scale-eater and a snail-eater - that rapidly diverged from a sympatric generalist ancestor within the last 10,000 years. While parallel evolution of gene expression driving convergent niche specialization seems common, we present, to our knowledge, the first example of significant parallel changes in expression coinciding with divergent niche specialization. 80% of genes that were differentially expressed between snail-eaters and generalists showed the same direction of expression in scale-eaters relative to generalists. Furthermore, parallel evolution in expression seem to be controlled by unique genetic variants in each specialist species. Genes showing parallel changes in expression were enriched for metabolic processes that may facilitate adaptation to a higher trophic level, while genes showing divergent expression likely shape the striking morphological differences between specialists. These findings contribute to a more nuanced understanding of convergent adaptations that arise during speciation, and highlight how species can evolve similar expression profiles adapted to divergent niches.

evolutionary biology↗

bioRxiv2018

Defining common principles of gene co-expression refines molecular stratification in cancer

Cancers converge onto shared patterns that arise from constraints placed by the biology of the originating cell lineage and microenvironment on recurrent programs driven by oncogenic events. This structure should be transferable to molecular stratification. We exploit expression data resources and a parsimonious and computationally efficient network analysis method to define consistent expression modules in colon and breast cancer. Comparison between cancer types identifies principles of gene co-expression: cancer hallmarks, functional and structural gene batteries, copy number variation and biology of originating lineage. Mapping outcome data at gene and module level onto these networks generates a detailed interactive resource. Testing the utility of the resulting modules in TCGA data defines specific associations of module expression with mutation state, identifying striking associations such as mast cell gene expression and mutation pattern in breast cancer. These analyses provide evidence for a generalizable framework to enhance molecular stratification in cancer.

bioinformatics↗

bioRxiv2026

Sequential Molecular Interactions Shape Aβ42 Aggregation, Propagation, and Toxicity

Protein aggregation is a context-dependent process in which the molecular environment can influence the properties of the resulting assemblies. In biological systems, these interactions can occur sequentially, as aggregates formed in one cellular or tissue context may encounter different molecular partners and act as seeds in subsequent aggregation events. Here, we used sequential seeding as a controlled experimental model of this temporal and contextual complexity to investigate how prion-like sequences from the gut microbiome modulate amyloid-{beta} aggregation across successive aggregation cycles. Combining kinetic, biophysical, conformational, and toxicity analyses, we show that early interactions with exogenous peptides modify the properties of first-generation A{beta}40- and A{beta}42-derived seeds, resulting in propagated A{beta}42 assemblies with distinct molecular and functional properties. These findings support an Interaction History model in which exogenous sequences bias the emergence of aggregate populations whose properties and subsequent propagation depend on the molecular contexts experienced during earlier aggregation events. Overall, our results present A{beta} aggregation as a history-dependent process and suggest that single-step assays may fail to capture aggregate diversity that emerges across successive aggregation cycles.

biochemistry↗

bioRxiv2017

A novel unbiased test for molecular convergent evolution and discoveries in echolocating, aquatic and high-altitude mammals

Distantly related species entering similar biological niches often adapt by evolving similar morphological and physiological characters. The extent to which genomic molecular convergence, and the extent to which coding mutations underlie this convergent phenotypic evolution remain unknown. Using a novel test, we ask which group of functionally coherent genes is most affected by convergent amino acid substitutions between phenotypically convergent lineages. This most affected sets reveals 75 novel coding convergences in important genes that pattern a highly adapted organ: the cochlea, skin and lung in echolocating, aquatic and high-altitude mammals, respectively. Our test explicitly requires the enriched converged term to not be simultaneously enriched for divergent mutations, and correctly dismisses relaxation-based signals, such as those produced by vision genes in subterranean mammals. This novel test can be readily applied to birds, fish, flies, worms etc., to discover more of the fascinating contribution of protein coding convergence to phenotype convergence.

evolutionary biology↗

bioRxiv2017

IndeCut evaluates performance of network motif discovery algorithms

Genomic networks represent a complex map of molecular interactions which are descriptive of the biological processes occurring in living cells. Identifying the small over-represented circuitry patterns in these networks helps generate hypotheses about the functional basis of such complex processes. Network motif discovery is a systematic way of achieving this goal. However, a reliable network motif discovery outcome requires generating random background networks which are the result of a uniform and independent graph sampling method. To date, there has been no sound practical method to numerically evaluate whether any network motif discovery algorithm performs as intended--thus it was not possible to assess the validity of resulting network motifs. In this work, we present IndeCut, the first and only method that allows characterization of network motif finding algorithm performance on any network of interest. We demonstrate that it is critical to use IndeCut prior to running any network motif finder for two reasons. First, IndeCut estimates the minimally required number of samples that each network motif discovery tool needs in order to produce an outcome that is both reproducible and accurate. Second, IndeCut allows users to choose the most accurate network motif discovery tool for their network of interest among many available options. IndeCut is an open source software package and is available at https://github.com/megrawlab/IndeCut.

systems biology↗

bioRxiv2017

RECONSTITUTION OF HELICAL SOLUBLE α-SYNUCLEIN THROUGH TRANSIENT INTERACTION WITH LIPID INTERFACES

-synuclein (Syn) is one of the key players in the pathogenesis of Parkinsons disease (PD) and other synucleinopathies. Its misfolding and subsequent aggregation into intracellular inclusions are the pathological hallmark of these diseases and may also play a central role in the molecular cascade leading to neurodegeneration. In this work, we report the existence of a novel soluble -helical conformer of Syn, an archetypal \"intrinsically disordered protein\" (IDP), obtained through transient interaction with lipid interfaces. We describe how the stability of this conformer is highly dependent on the continuous, dynamic oligomerization of the folded species. The conformational space of Syn appears to be highly context-dependent, and lipid bilayers might play crucial roles as molecular chaperones for cytosolic species in a cellular environment, as they do in the case of this previously unreported structure.\n\nSignificance StatementBoth genetic and histopathologic evidence tie -synuclein (Syn) to the pathogenesis of Parkinsons disease (PD), a widespread neurodegenerative disorder. Lipids play a central role in the dynamics of Syn in physiology and disease. Syn undergoes a coil-to-helix transition when binding to lipid vesicles and it is involved in the regulation of synaptic vesicle trafficking. Furthermore, recently discovered -helical, aggregation-resistant \"multimers\" of Syn could constitute a protective conformational pathway. We report the existence of a folded, lipid-unbound Syn conformer that forms upon transient interaction with lipids and is stabilized by dynamic homooligomerization, suggesting that synaptic activity could modulate resistance towards aggregation. Our results are therefore important both for the molecular pathology of PD and the structural biology of intrinsically disordered proteins.

biophysics↗

bioRxiv2018

Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes

It is widely assumed that cells must be physically isolated to study their molecular profiles. However, intact tissue samples naturally exhibit variation in cellular composition, which drives covariation of cell-class-specific molecular features. By analyzing transcriptional covariation in 7221 intact CNS samples from 840 individuals representing billions of cells, we reveal the core transcriptional identities of major CNS cell classes in humans. By modeling intact CNS transcriptomes as a function of variation in cellular composition, we identify cell-class-specific transcriptional differences in Alzheimers disease, among brain regions, and between species. Among these, we show that PMP2 is expressed by human but not mouse astrocytes and significantly increases mouse astrocyte size upon ectopic expression in vivo, causing them to more closely resemble their human counterparts. Our work is available as an online resource (http://oldhamlab.ctec.ucsf.edu) and provides a generalizable strategy for determining the core molecular features of cellular identity in intact biological systems.

neuroscience↗

bioRxiv2018

Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the "Disease Module Identification DREAM Challenge", an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).

bioinformatics↗

bioRxiv2018

PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data

The increasing availability of multi-omic platforms poses new challenges to data analysis. Joint visualization of multi-omics data is instrumental to understand interconnections across molecular layers and to fully leverage the biology discovery power offered by the multi-omics approach.\n\nWe present here PaintOmics 3, a web-based resource for the integrated visualization of multiple omic data types onto KEGG pathway diagrams. PaintOmics 3 combines server-end capabilities for data analysis with the potential of modern web resources for data visualization, providing researchers with a powerful framework for interactive exploration of their multi-omics information.\n\nUnlike other visualization tools, PaintOmics 3 covers a complete pathway analysis workflow, including automatic feature name/identifier conversion, multi-layered feature matching, pathway enrichment, network analysis, interactive heatmaps, trend charts, etc. It accepts a wide variety of omic types, including transcriptomics, proteomics and metabolomics, as well as region-based approaches such as ATAC-seq or ChIP-seq data. The tool is freely available at http://bioinfo.cipf.es/paintomics/.

bioinformatics↗

bioRxiv2018

Characterization of fluorescent proteins, promoters, and selectable markers for applications in the Lyme disease spirochete Borrelia burgdorferi

Lyme disease is the most widely reported vector-borne disease in the United States. Its incidence is rapidly increasing and disease symptoms can be debilitating. The need to understand the biology of the disease agent, the spirochete Borrelia burgdorferi, is thus evermore pressing. Despite important advances in B. burgdorferi genetics, the array of molecular tools available for use in this organism remains limited, especially for cell biological studies. Here, we adapt a palette of bright and mostly monomeric fluorescent proteins for versatile use and multi-color imaging in B. burgdorferi. We also characterize two novel antibiotic selection markers and establish the feasibility of their use in conjunction with extant markers. Lastly, we describe a set of constitutively active promoters of low and intermediate strengths that allow fine-tuning of gene expression levels. These molecular tools complement and expand current experimental capabilities in B. burgdorferi, which will facilitate future investigation of this important human pathogen. To showcase the usefulness of these reagents, we used them to investigate the subcellular localization of BB0323, a B. burgdorferi lipoprotein essential for survival in the host and vector environments. We show that BB0323 accumulates at the cell poles and future division sites of B. burgdorferi cells, highlighting the complex subcellular organization of this spirochete.\n\nIMPORTANCEGenetic manipulation of the Lyme disease spirochete B. burgdorferi remains cumbersome, despite significant progress in the field. The scarcity of molecular reagents available for use in this pathogen has slowed research efforts to study its unusual biology. Of interest, B. burgdorferi displays complex cellular organization features that have yet to be understood. These include an unusual morphology and a highly fragmented genome, both of which are likely to play important roles in the bacteriums transmission, infectivity, and persistence. Here, we complement and expand the array of molecular tools available for use in B. burgdorferi by generating and characterizing multiple fluorescent proteins, antibiotic selection markers, and constitutively active promoters of different strengths. These tools will facilitate investigations in this important human pathogen, as exemplified by the polar and midcell localization of the cell envelope regulator BB0323, which we uncovered using these reagents.

microbiology↗

bioRxiv2018

Molecular noise shapes bacteria-phage ecologies

Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their steady state population size, with the first strategy favoring simple and the second strategy favoring complex bacterial innate immunity.

biophysics↗

bioRxiv2018

K-Ras G-domain binding with signaling lipid phosphoinositides: PIP2 association, orientation, function

Ras genes are potent drivers of human cancers, with mutated K-Ras4B being the most abundant isoform. Targeted inhibition of oncogenic gene products is considered the holy grail of present-day cancer therapy, and recent discoveries of small molecule inhibitors for K-Ras4B greatly benefited from a deeper understanding of the protein structure and dynamics of the GTPase. Since interactions with biological membranes are key for Ras function, the details of Ras - lipid interactions have become a major focus of study, especially since it is becoming clear that such interactions not only involve the Ras C-terminus for lipid anchoring, but also the G-protein domain. Here we investigated the interaction between K-Ras4B with the signaling lipid phosphatidyl inositol (4,5) phosphate (PIP2) using NMR spectroscopy and molecular dynamics simulations, complemented by biophysical and cell biology assays. We discovered that the {beta}2 and {beta}3 strands as well as helices 4 and 5 of the GTPase G-domain bind to PIP2, and that these secondary structural elements employ specific residues for these interactions. These likely occur in two orientation states of the protein relative to the membrane. Importantly, we found that some of these residues, which are known to be oncogenic when mutated (D47K, D92N, K104M and D126N), are critical for K-Ras-mediated transformation of fibroblast cells, while not substantially affecting basal and assisted nucleotide hydrolysis and exchange. We further showed that mutation K104M can indeed abolish localization of mutant K-Ras to the plasma membrane. These findings suggest that specific G-domain residues play an important, previously-unknown role in regulating Ras function by mediating interactions with membrane PIP2 lipids. Thus, a detailed description of the novel K-Ras-PIP2 binding surfaces is likely to inform the future design of therapeutic reagents.

biophysics↗

bioRxiv2016

Discrete step sizes of molecular motors lead to bimodal non-Gaussian velocity distributions under force

Fluctuations in the physical properties of biological machines are inextricably linked to their functions. Distributions of run-lengths and velocities of processive molecular motors, like kinesin-1, are accessible through single molecule techniques, yet there is lack a rigorous theoretical model for these probabilities up to now. We derive exact analytic results for a kinetic model to predict the resistive force (F) dependent velocity (P(v)) and run-length (P(n)) distribution functions of generic finitely processive molecular motors that take forward and backward steps on a track. Our theory quantitatively explains the zero force kinesin-1 data for both P(n) and P(v) using the detachment rate as the only parameter, thus allowing us to obtain the variations of these quantities under load. At non-zero F, P(v) is non-Gaussian, and is bimodal with peaks at positive and negative values of v. The prediction that P(v) is bimodal is a consequence of the discrete step-size of kinesin-1, and remains even when the step-size distribution is taken into account. Although the predictions are based on analyses of kinesin-1 data, our results are general and should hold for any processive motor, which walks on a track by taking discrete steps.

Biophysics↗

bioRxiv2018

Antioxidant activity and phycoremediation ability of four cyanobacterial isolates obtained from a stressed aquatic system

Cyanobacteria are natural enormous sources of various biologically active compounds with great contributions in different industries. This study aimed to introduce molecular and biochemical characterization for four novel cyanobacterial isolates obtained from Egyptian wastewater canals. Besides, In vitro biological activity of these isolates and their potential ability to take up nutrients and heavy metals from wastewater were examined. The obtained accession numbers were KY250420.1, KY321359.1, KY296359.1 and KU373076.1 for Nostoc calcicola, Leptolyngbya sp, Nostoc sp, and Nostoc sp, respectively. The isolate Leptolyngbya sp (KY321359.1) showed the lowest identity (90%) with other deposited sequences in database. While the isolate Nostoc sp (KU373076.1) showed the highest total phenolic content as well as the highest levels of caffeic, ferulic and gallic acids. Consequently, it appeared the highest antioxidant scavenging activity. All cyanobacterial isolates revealed potent ability to take up nutrients and heavy metals from wastewater. Generally, this study provides a taxonomic and molecular evidence for four novel cyanobacterial isolates with antioxidant activity and potent phycoremediation ability.

genetics↗

bioRxiv2016

Global changes in patterning, splicing and primate specific lncRNAs in autism brain

We apply transcriptome-wide RNA sequencing in postmortem autism spectrum disorder (ASD) brain and controls and identify convergent alterations in the noncoding transcriptome, including primate specific lncRNA, and transcript splicing in ASD cerebral cortex, but not cerebellum. We characterize an attenuation of patterning between frontal and temporal cortex in ASD and identify SOX5, a transcription factor involved in cortical neuron fate specification, as a likely driver of this pattern. We further show that a genetically defined subtype of ASD, Duplication 15q Syndrome, shares the core transcriptomic signature of idiopathic ASD, indicating that observed molecular convergence in autism brain is the likely consequence of manifold genetic alterations. Using co-expression network analysis, we show that diverse forms of genetic risk for ASD affect convergent, independently replicated, biological pathways and provide an unprecedented resource for understanding the molecular alterations associated with ASD in humans.

Preprint↗

bioRxiv2018

Molecular phenotyping using networks, diffusion, and topology: soft tissue sarcoma

Many biological datasets are high-dimensional yet manifest an underlying order. In this paper, we describe an unsupervised data analysis methodology that operates in the setting of a multivariate dataset and a network which expresses influence between the variables of the given set. The technique involves network geometry employing the Wasserstein distance, global spectral analysis in the form of diffusion maps, and topological data analysis using the Mapper algorithm. The prototypical application is to gene expression profiles obtained from RNA-Seq experiments on a collection of tissue samples, considering only genes whose protein products participate in a known pathway or network of interest. Employing the technique, we discern several coherent states or signatures displayed by the gene expression profiles of the sarcomas in the Cancer Genome Atlas along the p53 signaling network. The signatures substantially recover the leiomyosarcoma, dedifferentiated liposarcoma (DDLPS), and synovial sarcoma histological subtype diagnoses, but they also include a new signature defined by simultaneous activation and inactivation of about a dozen genes, including activation of fibrinolysis inhibitor SERPINE1/PAI and inactivation of p53-family tumor suppressor gene P73 along with cyclin dependent kinase inhibitor 2A CDKN2A/P14ARF.

cancer biology↗

bioRxiv2017

Neurogenic decisions require a cell cycle independent function of the CD25B phosphatase

A fundamental issue in developmental biology and in organ homeostasis is understanding the molecular mechanisms governing the balance between stem cell maintenance and differentiation into a specific lineage. Accumulating data suggest that cell cycle dynamics plays a major role in the regulation of this balance. Here we show that the G2/M cell cycle regulator CDC25B phosphatase is required in mammals to finely tune neuronal production in the neural tube. We show that in chick neural progenitors, CDC25B activity is both required and sufficient to stimulate neurogenic divisions and to promote neuronal differentiation. We design a mathematical model showing that within a limited period of time, cell cycle length modifications cannot account for changes in the ratio of the mode of division. Using a CDC25B point mutation that cannot interact with CDK, we show that part of CDC25B activity on neurogenic divisions is independent of its action on the cell cycle.

developmental biology↗

bioRxiv2018

Deterministic Nature of Cellular Position Noise During C. elegans Embryogenesis

Individuals with identical genotypes exhibit great phenotypic variability known as biological noise, which has broad implications. While molecular-level noise has been extensively studied, in-depth analysis of cellular-level noise is challenging. Here, we present a systems-level quantitative and functional analysis of noise in cellular position during embryogenesis, an important phenotype indicating differentiation and morphogenesis. We show that cellular position noise is deterministic, stringently regulated by intrinsic and extrinsic mechanisms. The noise level is determined by cell lineage identity and is coupled to developmental properties including embryonic localization, cell contact, and left-right symmetry. Cells follow a concordant low-high-low pattern of noise dynamics, and fate specification triggers a global down-regulation of noise that provide a noise-buffering strategy. Noise is stringently regulated throughout embryogenesis, especially during cell division and cell adhesion and gap junctions function to restrict noise. Collectively, our study reveals system properties and regulatory mechanisms of cellular noise control during development.

developmental biology↗