title: Hierarchical Computational Anatomy: Unifying the Molecular to Tissue Continuum via Measure Representations of the Brain

abstract:
ObjectiveThe objective of this research is to unify the molecular representations of spatial transcriptomics and cellular scale histology with the tissue scales of Computational Anatomy for brain mapping.

Impact statementWe present a unified representation theory for brain mapping based on geometric measures of the micro-scale phenotypes of molecular disease simultaneously with the connectomic scales of complex interacting brain circuits.

IntroductionMapping across coordinate systems in computational anatomy allows us to understand structural and functional properties of the brain at the millimeter scale. New measurement technologies in digital pathology and spatial transcriptomics allow us to measure the brain molecule by molecule and cell by cell based on protein and transcriptomic identity. We currently have no mathematical representations for integrating consistently the tissue limits with the molecular particle descriptions. The formalism derived here demonstrates the methodology for transitioning consistently from the molecular scale of quantized particles - as first introduced by Dirac as the class of generalized functions - to the continuum and fluid mechanics scales appropriate for tissue.

MethodsWe introduce two methods based on notions of generalized function geometric measures and statistical mechanics. We use generalized functions expanded to include functional geometric descriptions - electrophysiology, transcriptomic, molecular histology - to represent the molecular biology scale integrated with a Boltzman like procedure to pass from the sparse particles to empirical probability laws on the functional state of the tissue.

ResultsWe demonstrate a unified mapping methodology for transferring molecular information in the transcriptome and histological scales to the human atlas scales for understanding Alzheimers disease.

ConclusionsWe demonstrate a unified brain mapping theory for molecular and tissue scales based on geometric measure representations.


title: Neuromodulation-induced burst firing in parvalbumin interneurons of the basolateral amygdala mediates transition between fear-associated network and behavioral states

abstract: Patterned coordination of network activity in the basolateral amygdala (BLA) is important for fear expression. Neuromodulatory systems play an essential role in regulating changes between behavioral states, however the mechanisms underlying the neuromodulatory control of BLA circuits that mediates transitions between brain and behavioral states remain largely unknown. We examined the role of neuromodulation of parvalbumin (PV)-expressing interneurons in the BLA in coordinating network and behavioral states using combined chemogenetics, ex vivo patch clamp recordings, and in vivo and ex vivo local field potential recordings. We show that Gq signaling, whether by the designer receptor, hM3D, 1A adrenoreceptors, or 5-HT2a serotonergic receptors, induces a previously undescribed, highly stereotyped bursting pattern of activity in BLA PV interneurons that generates synchronous bursts of inhibitory postsynaptic currents and phasic firing in the BLA principal neurons. The Gq activation in PV interneurons induced a transition from tonic to phasic firing in the BLA PV neurons and principal neurons and suppressed BLA gamma oscillations in slices and suppressed BLA gamma and potentiated theta power in vivo. Gq activation in BLA PV interneurons also facilitated fear memory recall, consistent with previous reports of BLA gamma suppression and theta potentiation during conditioned fear expression. Thus, our data reveal a BLA parvalbumin neuron-specific Gq neuromodulatory mechanism that mediates the transition to a fear-associated network and behavioral state.

category: neuroscience


title: Spatial alignment between faces and voices improves selective attention to audio-visual speech

abstract: The ability to see a talkers face has long been known to improve speech intelligibility in noise. This perceptual benefit depends on approximate temporal alignment between the auditory and visual speech components. However, the practical role that cross-modal spatial alignment plays in integrating audio-visual (AV) speech remains unresolved, particularly when competing talkers are present. In a series of online experiments, we investigated the importance of spatial alignment between corresponding faces and voices using a paradigm that featured both acoustic masking (speech-shaped noise) and attentional demands from a competing talker. Participants selectively attended a Target Talkers speech, then identified a word spoken by the Target Talker. In Exp. 1, we found improved task performance when the talkers faces were visible, but only when corresponding faces and voices were presented in the same hemifield (spatially aligned). In Exp. 2, we tested for possible influences of eye position on this result. In auditory-only conditions, directing gaze toward the distractor voice reduced performance as predicted, but this effect could not fully explain the cost of AV spatial misalignment. Finally, in Exp. 3 and 4, we show that the effect of AV spatial alignment changes with noise level, but this was limited by a floor effect: due to the use of closed-set stimuli, participants were able to perform the task relatively well using lipreading alone. However, comparison between the results of Exp. 1 and Exp. 3 suggests that the cost of AV misalignment is larger at high noise levels. Overall, these results indicate that spatial alignment between corresponding faces and voices is important for AV speech integration in attentionally demanding communication settings.


title: Prostaglandin E2 directly inhibits the conversion of inducible regulatory T cells through EP2 and EP4 receptors via antagonizing TGF-β signalling

abstract:
Background and PurposeRegulatory T (Treg) cells are essential for control of inflammatory processes by suppressing Th1 and Th17 cells. The bioactive lipid mediator prostaglandin E2 (PGE2) promotes inflammatory Th1 and Th17 cells and exacerbates T cell-mediated autoimmune diseases. However, the actions of PGE2 on the development and function of Treg cells, particularly under inflammatory conditions, are debated. In this study, we examined whether PGE2 had a direct action on T cells to modulate de novo differentiation of Treg cells.

Experimental ApproachWe employed an in vitro T cell culture system of TGF-{beta}-dependent Treg induction from naive T cells. PGE2 and selective agonists for its receptors, and other small molecular inhibitors were used. Mice with specific lack of EP4 receptors in T cells were used to assess Treg cell differentiation in vivo. Human peripheral blood T cells from healthy individuals were used to induce differentiation of inducible Treg cells.

Key ResultsTGF-{beta}-induced Foxp3 expression and Treg cell differentiation in vitro was markedly inhibited by PGE2, which was due to interrupting TGF-{beta} signalling. EP2 or EP4 agonism mimicked suppression of Foxp3 expression in WT T cells, but not in T cells deficient in EP2 or EP4, respectively. Moreover, deficiency of EP4 in T cells impaired iTreg cell differentiation in vivo. PGE2 also appeared to inhibit the conversion of human iTreg cells.

Conclusion and ImplicationsOur results show a direct, negative regulation of iTreg cell differentiation by PGE2, highlighting the potential for selectively targeting the PGE2-EP2/EP4 pathway to control T cell-mediated inflammation.

What is already knownPGE2 promotes inflammatory Th1 and Th17 cells and facilitates T cell-mediated immune inflammation, but the action of PGE2 on Treg cells is debated.

What does this study addPGE2 directly acts on T cells to inhibit inducible Treg cell differentiation in vitro and in vivo through its receptors EP2 and EP4 and by antagonising TGF-{beta} signalling.

What is the clinical significanceTherapeutically blocking the EP4 receptor may be beneficial for management of T cell-mediated autoimmune inflammation.

category: immunology


title: Endothelial SIRPα signaling controls thymic progenitor homing for T cell regeneration and antitumor immunity

abstract:
Thymic homing of hematopoietic progenitor cells (HPCs) is an essential step for the subsequent T cell development. Previously we have identified a subset of specialized thymic portal endothelial cells (TPECs), which is important for thymic HPC homing. However, the underlying molecular mechanism remains still unknown. Here we found that signal regulatory protein alpha (SIRP) is preferentially expressed on TPECs. Disruption of CD47-SIRP signaling in mice resulted in reduced number of thymic early T cell progenitors (ETPs) and impaired thymic HPC homing. Mechanistically, SIRP-deficient ECs and CD47-deficient lymphocytes demonstrated impaired transendothelial migration (TEM). Specifically, SIRP intracellular ITIM motif-initiated downstream signaling in ECs was found to be required for TEM in a SHP2- and Src-dependent manner. Furthermore, CD47-signaling from migrating cells and SIRP intracellular signaling were found to be required for VE-cadherin endocytosis in ECs. Functionally, SIRP signaling is required for T cell regeneration upon sub-lethal total body irradiation (SL-TBI); CD47-SIRP signaling blockade post SL-TBI diminishes antitumor immunity. Thus, our study reveals a novel role of endothelial SIRP signaling for thymic HPC homing for T cell regeneration and antitumor immunity.

Graphic abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/440464v1_ufig1.gif" ALT="Figure 1">
View larger version (23K):
org.highwire.dtl.DTLVardef@d53edorg.highwire.dtl.DTLVardef@100f2c9org.highwire.dtl.DTLVardef@1438a6forg.highwire.dtl.DTLVardef@135aa2b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Thymic homing of hematopoietic progenitor cells is fundamental to the T cell-based adaptive immunity, yet the molecular basis of this process is less clear. We discovered that endothelial SIRP signaling, engaged by migrating cell derived CD47 ligand, regulates thymic homing of hematopoietic progenitor cells for T cell regeneration and antitumor immunity.

O_LISIRP is preferentially expressed on thymic portal endothelial cells.
C_LIO_LIEndothelial SIRP regulates thymic homing of hematopoietic progenitor cells.
C_LIO_LICD47-SIRP downstream signaling induces VE-cadherin endocytosis.
C_LIO_LICD47-SIRP signaling blockade impairs thymic T cell regeneration and antitumor immunity.
C_LI


title: CFH loss in human RPE cells leads to inflammation and complement system dysregulation via the NF-B pathway

abstract: Age-related macular degeneration (AMD), the leading cause of vision loss in the elderly, is a degenerative disease of the macula, where retinal pigment epithelium (RPE) cells are damaged in the early stages of the disease and chronic inflammatory processes may be involved. Besides ageing and lifestyle factors as drivers of AMD, a strong genetic association to AMD is found in genes of the complement system, with a single polymorphism in the complement factor H gene (CFH), accounting for the majority of AMD risk. However, the exact mechanism by which CFH dysregulation confers such a great risk for AMD and its role in RPE cells homeostasis is unclear. To explore the role of endogenous CFH locally in RPE cells, we silenced CFH in human hTERT-RPE1 cells. We demonstrate that endogenously expressed CFH in RPE cells modulates inflammatory cytokine production and complement regulation, independent of external complement sources or stressors. We show that loss of the factor H protein (FH) results in increased levels of inflammatory mediators (e.g. IL-6, IL-8, GM-CSF) and altered levels of complement proteins (e.g. C3, CFB upregulation and C5 downregulation) that are known to play a role in AMD. Moreover, we identified the NF-{kappa}B pathway as the major pathway involved in the regulation of these inflammatory and complement factors. Our findings suggest that in RPE cells, FH and the NF-{kappa}B pathway work in synergy to maintain inflammatory and complement balance and in case either one of them is dysregulated, the RPE microenvironment changes towards a pro-inflammatory AMD-like phenotype.


title: Individualized VDJ recombination predisposes the available Ig sequence space

abstract: The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individuals naive Ig repertoire, and consequently (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual-specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also non-genetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.


title: Active Rheumatoid Arthritis in a Mouse Model is not an Independent Risk Factor for Periprosthetic Joint Infection

abstract:
IntroductionPeriprosthetic joint infection (PJI) represents a devastating complication of total joint arthroplasty associated with significant morbidity and mortality. Literature suggests a possible higher incidence of periprosthetic joint infection (PJI) in patients with rheumatoid arthritis (RA). There is, however, no consensus on this relative risk nor a well-defined mechanism of this purported risk. This study investigates how collagen-induced arthritis (CIA), a validated animal model of RA, impacts infectious burden in a well-established model of PJI.

MethodsControl mice were compared against CIA mice. Whole blood samples were collected to quantify systemic IgG levels via ELISA. Ex vivo respiratory burst function was measured via dihydrorhodamine assay. Ex vivo Staphylococcus aureus Xen36 burden was measured directly via colony forming unit (CFU) counts and crystal violet assay to assess biofilm formation. In vivo, surgical placement of a titanium implant through the knee joint and inoculation with S. aureus Xen36 was performed. Bacterial burden was then quantified by longitudinal bioluminescent imaging.

ResultsMice with CIA demonstrated significantly higher levels of systemic IgG compared with control mice (p = 0.003). Ex vivo, there was no significant difference in respiratory burst function (p=0.89) or S. aureus bacterial burden as measured by CFU counts (p=0.91) and crystal violet assay (p=0.96). In vivo, no significant difference in bacterial bioluminescence between groups was found at all postoperative time points. CFU counts of both the implant and the peri-implant tissue were not significantly different between groups (p=0.82 and 0.80, respectively).

ConclusionThis study demonstrated no significant difference in S. aureus infectious burden between mice with CIA and control mice. These results suggest that untreated, active RA may not represent a significant intrinsic risk factor for PJI. Further mechanistic translational and clinical studies are, however, warranted to thoroughly investigate the infectious risk of RA.


title: Spatially resolved analysis of Pseudomonas aeruginosa biofilm proteomes measured by laser ablation sample transfer

abstract: Heterogeneity in the distribution of nutrients and O2 gradients during biofilm growth gives rise to changes in phenotype. There has been long term interest in identifying spatial differences during biofilm development including clues that identify chemical heterogeneity. Laser ablation sample transfer (LAST) allows site-specific sampling combined with label free proteomics to distinguish radially and axially resolved proteomes for Pseudomonas aeruginosa biofilms. Specifically, differential protein abundances on oxic vs. anoxic regions of a biofilm was observed by combining LAST with bottom up proteomics. This study reveals active metabolism in the anoxic region of the biofilm with respect to the oxic region in P. aeruginosa, an aerobe by nature. Protein abundance data related to cellular acclimations to chemical gradients include identification of glucose catabolizing proteins, high abundance of proteins from arginine and polyamine metabolism, and proteins that could also support virulence and environmental stress mediation on the anoxic region. Finally, this methodology requires only a few mm2 of biofilm area to identify hundreds of proteins.

category: microbiology


title: Distribution, prevalence, and causative agents of fungal keratitis: A systematic review and meta-analysis (1990 to 2020)

abstract: Fungal keratitis is a sight-threatening infection with global distribution. In this systematic review and meta-analysis we collected all the articles with data on the prevalence of fungal keratitis among various patient groups from January 1, 1990 to May 27, 2020. The 169 eligible articles were divided into 6 groups. The pooled prevalence was variable with values ranging from 0.05% among post-keratoplasty patients to 43.01% among patients with a clinical suspicion of fungal keratitis. Except for post-keratoplasty cases (yeast: 51.80%), in all patient groups moulds were more common than yeasts. Although more than 50 distinct species of fungi have been found to cause fungal keratitis, Fusarium species followed by Aspergillus species were the most common causes of the disease. In general, 9.29% (95% CI 6.52, 12.38) of fungal keratitis cases were mixed with bacterial agents.


title: A bacterial "shield and sword": A previously uncharacterized two-component system protects uropathogenic Escherichia coli from host-derived oxidative insults and promotes hemolysin-mediated host cell pyroptosis

abstract: Uropathogenic Escherichia coli (UPEC) deploys an array of virulence factors to successfully establish urinary tract infections. Coordinated expression of these various virulence factors is critical for UPECs overall fitness in the host. Two-component signaling systems (TCSs) are a major mechanism by which bacteria sense environmental cues and initiate adaptive responses. Here, we report a previously uncharacterized TCS encoded on a pathogenicity island in UPEC that directly activates the expression of a putative methionine sulfoxide reductase system (C3566/C3567) and a pore-forming -hemolysin in response to host-derived hydrogen peroxide (H2O2) exposure. The TCS increases UPEC resistance to H2O2 in vitro and survival in macrophages in tissue culture via C3566/C3567. Additionally, the TCS mediates -hemolysin-induced renal epithelial cell and macrophage death via a pyroptosis pathway. Taken together, our data suggest a paradigm in which this signal transduction system coordinates both bacterial pathogen defensive and offensive traits in the presence of host-derived signals.


title: Characterization of changes in the hemagglutinin that accompanied the emergence of H3N2/1968 pandemic influenza viruses

abstract: The hemagglutinin (HA) of A/H3N2 pandemic influenza viruses (IAVs) of 1968 differed from its inferred avian precursor by eight amino acid substitutions. To determine their phenotypic effects, we studied recombinant variants of A/Hong Kong/1/1968 virus containing either human-type or avian-type amino acids in the corresponding positions of HA. The precursor HA displayed receptor binding profile and high conformational stability typical for duck IAVs. Substitutions Q226L and G228S, in addition to their known effects on receptor specificity and replication, marginally decreased HA stability. Substitutions R62I, D63N, D81N and N193S reduced HA binding avidity. Substitutions R62I, D63N, D81N and A144G promoted virus replication in human airway epithelial cultures. Analysis of HA sequences revealed that substitutions D63N and D81N accompanied by the addition of N-glycans represent common markers of avian H3 HA adaptation to mammals. Our results advance understanding of genotypic and phenotypic changes in IAV HA required for avian-to-human adaptation and pandemic emergence.


title: Nuclear retention of pre-mRNA involving Cajal bodies during meiotic prophase in plants

abstract: Gene regulation ensures that the appropriate genes are expressed at the proper times. Nuclear retention of incompletely spliced or mature mRNAs emerges as a novel, previously underappreciated layer of post-transcriptional gene regulation. Studies on this phenomenon indicated that it exerted significant impact on the regulation of gene expression by regulating export and translation delay, which allows synthesis of specific proteins in response to a stimulus, e.g. under stress conditions or at strictly controlled time points, e.g. during cell differentiation or development. Here, we found that transcription in microsporocytes, during prophase of the first meiotic division, occurs in pulsatile manner. After each pulse, the transcriptional activity is silenced, but the transcripts synthesized at this time are not exported immediately to the cytoplasm, but are retained in the nucleoplasm and Cajal bodies (CBs). In contrast to nucleoplasm, mature transcripts were not found in CBs. Only non-fully-spliced transcripts with retained introns were stored in the CBs. Retained introns are spliced at precisely defined times, and fully mature mRNAs are released into the cytoplasm, where the proteins are produced. These proteins are necessary for further cell development during meiotic prophase. Our findings provide new insight into the regulatory mechanisms of gene expression based on mRNA retention in the nucleus during the development of generative cells in plants. Similar processes were observed during spermatogenesis in animals. This indicates the existence of an evolutionarily conserved mechanism of gene expression regulation during generative cells development in Eukaryota.

category: cell biology


title: Cell division in tissues enables macrophage infiltration

abstract: Migration of cells through diverse tissues is essential for development, immune response and cancer metastasis 1-3. To reach their destination, cells must overcome the resistance imposed by complex microenvironments, composed of neighboring cells and extracellular matrix (ECM)4-6. While migration through pores and tracks in ECM has been well studied 4,5,7, little is known about cellular traversal into confining cell-dense tissues. Here by combining quantitative live imaging with genetic and optogenetic perturbations we identify a crucial role for cell division during cell migration into tissues. We find that normal embryonic invasion by Drosophila macrophages between the ectoderm and mesoderm8,9 absolutely requires division of an epithelial ectodermal cell at the site of entry. Dividing ectodermal cells disassemble ECM attachment formed by Integrin-mediated focal adhesions next to mesodermal cells, allowing macrophages to move their nuclei ahead and invade. Decreasing or increasing the frequency of ectodermal division correspondingly either hinders or promotes macrophage invasion. Reducing the levels of focal adhesion components in the ectoderm allows macrophage entry even in the absence of division. Our study demonstrates the critical importance of division at the entry site to enable in vivo cell invasion by relieving the steric impediment caused by focal adhesions. We thus provide a new perspective on the regulation of cellular movement into tissues.


title: Multiparametric assessment of cellular lipid metabolism in hypercholesterolemia

abstract:
Systematic insight into cellular dysfunctions can improve understanding of disease etiology, risk assessment and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validated this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrated lipid storage data into a novel readout, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlated positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explained hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking from a few mls of blood and is applicable to dissect metabolic disorders, such as hypercholesterolemia.

MotivationWe have limited information on how cellular lipid uptake and processing differ between individuals and influence the development of metabolic diseases, such as hypercholesterolemia. Available assays are labor intensive, require skilled personnel and are difficult to scale to higher throughput, making it challenging to obtain systematic functional cell-based data from individuals. To overcome this problem, we established a scalable automated analysis pipeline enabling reliable quantification of multiple cellular readouts, including lipid uptake, storage and mobilization, from different white blood cell populations. This approach provides new personalized insights into the cellular basis of hypercholesterolemia and obesity.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/440471v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@9222c1org.highwire.dtl.DTLVardef@27e289org.highwire.dtl.DTLVardef@89ba82org.highwire.dtl.DTLVardef@33c9cd_HPS_FORMAT_FIGEXP  M_FIG C_FIG


title: Multiparametric profiling of cellular lipid metabolism in hypercholesterolemia


title: Multiparametric Platform for Profiling Lipid Trafficking in Human Leukocytes: Application for Hypercholesterolemia


title: Neurodevelopment vs. the immune system: complementary contributions of maternally-inherited gene transcripts and proteins to successful egg development in fish

abstract:
BackgroundIn Metazoans, embryonic development relies on maternally-inherited mRNAs and proteins that are critical for early developmental success and known to play major roles at later stages, beyond zygotic genome activation. However, very poor concordance between transcript and protein levels in oocytes and embryos of vertebrates suggest that maternally-inherited proteins and maternally-inherited mRNAs are playing different roles in unfertilized eggs, not considered to date comprehensively. The aim of this study was to investigate the respective contribution of maternally-inherited mRNAs and maternally-inherited proteins to egg molecular cargo and to its developmental competence using pikeperch, an ecologically and commercially relevant freshwater fish species, as a model.

ResultsOur data shed new light on the importance of maternally-inherited mRNAs in nervous system development suggesting that neurogenesis is a major mRNA-dependent non-genetic inheritance factor. In contrast, our results highlight a specific role of maternally-inherited proteins in immune response in ovulated eggs suggesting that maternal proteins would rather contribute to developmental success through protection of the embryo against pathogens. Further analysis revealed susceptibility of the transcriptome to modifications during the post-vitellogenic processes (i.e., final oocyte maturation and ovulation), whereas proteomic cargo remains unaffected. This may negatively affect developmental competence of the egg and possibly influence further nervous system development of the embryo.

ConclusionsOur study provides novel insights into the understanding of type-specific roles of maternally-inherited molecules in fish. Here we show, for the first time, that transcripts and proteins have distinct, yet complementary, functions in the egg of teleost fish. Maternally-inherited mRNAs would shape embryo neurodevelopment and possibly the future behavior of the fish, while maternally-inherited proteins would rather be responsible for protecting the embryo against pathogens. Additionally, we observed that processes directly preceding ovulation may considerably affect the reproductive success by modifying expression level of genes crucial for proper embryonic development, being novel fish egg quality markers (e.g., smarca4 or h3f3a). These results are of major importance for understanding the influence of external factors on reproductive fitness in both captive and wild-type fish species.

category: developmental biology


title: Contrasting impacts of environmental variability on the breeding biology of two sympatric small procellariiform seabirds in south-eastern Australia

abstract: Seabirds play a vital role in marine ecosystems and are determinant sentinels of the productivity of their environments. The long-term study of their breeding biology and their responses to environmental variations can be used to monitor the effects of climate change on marine fauna. However, the ecological and physiological differences among seabirds induce a large range of responses complicating our understanding of the effects of environmental changes on marine ecosystems. The present study investigated the impact of environmental variability on breeding biology in two sympatric small Procellariiform species, the fairy prion (Pachyptila turtur) and the common diving petrel (Pelecanoides urinatrix), over four reproductive seasons (2017-2020) in Bass Strait, south-eastern Australia. Marine heatwaves had a negative effect on chick growth, breeding success, and induced a delay in laying dates in both species. While fairy prions maintained a relatively high breeding success and broadly constant breeding phenology, common diving petrels delayed the start of the breeding season by up to 50 days and experienced dramatic collapses in breeding success in years of high marine heat wave occurrence. The high wing loading and absence of stomach oils in the common diving petrel are likely to have limited the capacity of this species to increase foraging effort in years of low food availability.


title: Local signaling specifies tissue-resident fibroblasts from multipotent sclerotome progenitors in zebrafish

abstract:
Fibroblasts play an important role in maintaining tissue integrity by secreting components of the extracellular matrix and initiating response to injury. Although the function of fibroblasts has been extensively studied in adults, the embryonic origin and diversification of different fibroblast subtypes during development remain largely unexplored. Using zebrafish as a model, we show that the sclerotome, a sub-compartment of the somite, is the embryonic source of multiple fibroblast populations, including tenocytes (tendon fibroblasts), blood vessel associated fibroblasts, and fin mesenchymal cells. High resolution imaging shows that different fibroblast subtypes occupy unique anatomical locations with distinct morphologies. Photoconversion-based cell lineage analysis reveals that sclerotome progenitors at different dorsal-ventral and anterior-posterior positions display distinct differentiation potentials. Single cell clonal analysis suggests that sclerotome progenitors are multipotent, and the fate of their daughter cells is biased by their migration paths and relative positions. Using a small molecule inhibitor, we show that BMP signaling is required for the development of fin mesenchymal cells in the peripheral fin fold. Together, our work demonstrates that the sclerotome contains multipotent progenitors that respond to local signals to generate a diverse population of tissue-resident fibroblasts.

AUTHOR SUMMARYFibroblasts are present in most organs in our body. They not only provide structural support to corresponding tissues, but also play important roles in wound healing and tissue fibrosis. Although the function of fibroblasts has been well appreciated, how different tissue-resident fibroblasts emerge during embryonic development is still poorly understood. Using the zebrafish model, we identify the sclerotome, a sub-compartment of the embryonic somite, as the main source of multiple fibroblast populations. Different fibroblast subtypes display distinct morphologies and locate at unique positions to support different tissues, including the muscles, blood vessels and the fin fold. Using cell tracing in live animals, we find that single sclerotome progenitors are able to generate more than one type of fibroblasts. The differentiation potential of sclerotome progenitors is biased by their initial locations in the trunk as well as their migration directions and relative positions. Local BMP signaling in the fin fold is essential for the proper development of sclerotome derived fin mesenchymal cells. Together, our results show that local microenvironment contributes to the diversification of multipotent sclerotome progenitors into distinct fibroblast subtypes.


title: Thermodynamic constraints on the diversity of microbial ecosystems

abstract:
Non-equilibrium thermodynamics has long been an area of substantial interest to ecologists because most fundamental biological processes, such as protein synthesis and respiration, are inherently energy-consuming. However, most of this interest has focused on developing coarse ecosystem-level maximisation principles, providing little insight into underlying mechanisms that lead to such emergent constraints. Microbial communities are a natural system to decipher this mechanistic basis because their interactions in the form of substrate consumption, metabolite production, and cross-feeding can be described explicitly in thermodynamic terms. Previous work has considered how thermodynamic constraints impact competition between pairs of species, but restrained from analysing how this manifests in complex dynamical systems. To address this gap, we develop a thermodynamic microbial community model with fully reversible reaction kinetics, which allows direct consideration of free-energy dissipation. This also allows species to interact via products rather than just substrates, increasing the dynamical complexity, and allowing a more nuanced classification of interaction types to emerge. Using this model, we find that community diversity increases with substrate lability, because greater free-energy availability allows for faster generation of niches. Thus, more niches are generated in the time frame of community establishment, leading to higher final species diversity. We also find that allowing species to make use of near-to-equilibrium reactions increases diversity in a low free-energy regime. In such a regime, two new thermodynamic interaction types that we identify here reach comparable strengths to the conventional (competition and facilitation) types, emphasising the key role that thermodynamics plays in community dynamics. Our results suggest that accounting for realistic thermodynamic constraints is vital for understanding the dynamics of real-world microbial communities.

Author summaryThere is a growing interest in microbial communities due to their important role in biogeochemical cycling as well as plant and animal health. Although our understanding of thermodynamic constraints on individual cells is rapidly improving, the impact of these constraints on complex microbial communities remains largely unexplored theoretically and empirically. Here, we develop a new microbial community model which allows thermodynamic efficiency and entropy production to be calculated directly. We find that availability of substrates with greater free-energy allows for a faster rate of niche generation, leading to higher final species diversity. We also show that when the free-energy availability is low, species with reactions close to thermodynamic equilibrium are favoured, leading to more diverse and efficient communities. In addition to the conventional interaction types (competition and facilitation), our model reveals the existence of two novel interaction types mediated by products rather than substrates. Though the conventional interactions are generally the strongest, the novel interaction types are significant when free-energy availability is low. Our results suggest that non-equilibrium thermodynamics need to be considered when studying microbial community dynamics.

category: ecology


title: Thermodynamic constraints on the assembly and diversity ofmicrobial ecosystems are different near to and far fromequilibrium


title: Thermodynamic constraints on the assembly and diversity of microbial ecosystems are different near to and far from equilibrium


title: occAssess: An R package for assessing potential biases in species occurrence data

abstract: Species occurrence records from a variety of sources are increasingly aggregated into heterogeneous databases and made available to ecologists for immediate analytical use. However, these data are typically biased, i.e. they are not a probability sample of the target population of interest, meaning that the information they provide may not be an accurate reflection of reality. It is therefore crucial that species occurrence data are properly scrutinised before they are used for research. In this article, we introduce occAssess, an R package that enables straightforward screening of species occurrence data for potential biases. The package contains a number of discrete functions, each of which returns a measure of the potential for bias in one or more of the taxonomic, temporal, spatial and environmental dimensions. Users can opt to provide a set of time periods into which the data will be split; in this case separate outputs will be provided for each period, making the package particularly useful for assessing the suitability of a dataset for estimating temporal trends in species distributions. The outputs are provided visually (as ggplot2 objects) and do not include a formal recommendation as to whether data are of sufficient quality for any given inferential use. Instead, they should be used as ancillary information and viewed in the context of the question that is being asked, and the methods that are being used to answer it. We demonstrate the utility of occAssess by applying it to data on two key pollinator taxa in South America: leaf-nosed bats (Phyllostomidae) and hoverflies (Syrphidae). In this worked example, we briefly assess the degree to which various aspects of data coverage appear to have changed over time. We then discuss additional applications of the package, highlight its limitations, and point to future development opportunities.


title: Deep Learning and trajectory representation for the prediction of seabird diving behaviour

abstract:
AO_SCPLOWBSTRACTC_SCPLOWAt-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as  fine-tuning. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation. To make easier such applications, we share online the different models we trained on the considered datasets (https://github.com/AmedeeRoy/BirdDL/models).

Author SummaryOver the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as  ready-to-use tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training.


title: Deep inference of seabird dives from GPS-only records: performance and generalization properties


title: A pilot study to define and identify future priorities into Allocasuarina robusta recovery as part of a community program

abstract: The Allocasuarina robusta pilot study investigated the process involved to facilitate seed recruitment as part of a threatened species project. Several experiments occurred, each examining a specific attribute in the seed recruitment process. A. robusta is a threatened species of national and local significance. The research design would help land managers and communities to conserve A. robusta. The investigation aimed to improve seed recruitment in A. robusta occurring under natural conditions. The experiment results highlighted several experimental design flaws and identified opportunities to increase community participation as part of the recovery program.


title: The role of competition versus cooperation in microbial community coalescence

abstract:
New microbial communities often arise through the mixing of two or more separately assembled parent communities, a phenomenon that has been termed "community coalescence". Understanding how the interaction structures of complex parent communities determine the outcomes of coalescence events is an important challenge. While recent work has begun to elucidate the role of competition in coalescence, that of cooperation, a key interaction type commonly seen in microbial communities, is still largely unknown. Here, using a general consumer-resource model, we study the combined effects of competitive and cooperative interactions on the outcomes of coalescence events. In order to do so, we simulate coalescence events between pairs of communities with different degrees of competition for shared carbon resources and cooperation through cross-feeding on leaked metabolic by-products (facilitation). We also study how structural and functional properties of post-coalescence communities evolve when they are subjected to repeated coalescence events. We find that in coalescence events, the less competitive and more cooperative parent communities contribute a higher proportion of species to the new community, because this endows superior ability to deplete resources and resist invasions. Consequently, when a community is subjected to repeated coalescence events, it gradually evolves towards being less competitive and more cooperative, as well as more species rich, robust and efficient in resource use. Encounters between microbial communities are becoming increasingly frequent as a result of anthropogenic environmental change, and there is great interest in how the coalescence of microbial communities affects environmental and human health. Our study provides new insights into the mechanisms behind microbial community coalescence, and a framework to predict outcomes based on the interaction structures of parent communities.

Author summaryIn nature, new microbial communities often arise from the fusion of whole, previously separate communities (community coalescence). Despite the crucial role that interactions among microbes play in the dynamics of complex communities, our ability to predict how these affect the outcomes of coalescence events remains limited. Here, using a general mathematical model, we study how the structure of species interactions confers an advantage upon a microbial community when it encounters another, and how communities evolve after undergoing repeated coalescence events. We find that competitive interactions between species preclude their survival upon a coalescence event, while cooperative interactions are advantageous for post-coalescence survival. Furthermore, after a community is exposed to many coalescence events, the remaining species become less competitive and more cooperative. Ultimately, this drives the community evolution, yielding post-coalescence communities that are more species-rich, productive, and resistant to invasions. There are many potential environmental and health implications of microbial community coalescence, which will benefit from the theoretical insights that we offer here about the fundamental mechanisms underlying this phenomenon.


title: The forest avifauna of Arabuko Sokoke Forest and adjacent modified habitats

abstract: Arabuko Sokoke Forest (ASF) is the largest area of coastal forest remaining in East Africa and a major Important Bird Area in mainland Kenya. The study analysed data from point count surveys over 15 months in three land use types; primary forest (PF), plantation forest (PL), and farmlands (FM), and compared these to the first comprehensive bird checklist for the forest, as well as recent surveys from other studies. Avifaunal diversity and abundance were compared using multivariate analysis to determine bird responses to different land use characteristics. The primary forest held a distinctive bird community, while the bird communities of farmlands and plantation forest were more similar to each other. Land use had a significant effect on overall avian diversity and abundance. The current forest avifauna was divided into forest specialists (16 species), forest generalists (26 species) and forest visitors (30 species). Seven species of forest specialist and generalists recorded prior to 1980 may no longer occur in the forest. Of 38 specialists and generalists recorded in our point counts, 19 were also recorded on farmland and 28 in plantations. One forest specialist, the Green Barbet, was most encountered outside the forest. Future research should focus on habitat use by these bird species, and the extent of movement by forest birds between the remaining patches of coastal forest. Patterns of habitat use by birds in the area suggest that vegetation heterogeneity and habitat complexity are especially significant in sustaining diverse and abundant bird populations. The management of plantations and farmland will be critical for the conservation of forest generalists and forest visitors.


title: Using ddRAD-seq phylogeography to test for genetic effects of headwater river capture in suckermouth armored catfish (Loricariidae: Hypostomus) from the central Brazilian Shield

abstract: River capture is a geological process of potentially great importance in shaping the genetic diversity, distributions, and community composition of freshwater taxa. Using phylogeographic analyses of ddRAD-seq data from suckermouth armored catfish (Hypostomus sp. 2) populations, we tested for predicted genetic effects of headwater river capture events in central Brazil, previously supported by geological and community ecological data. We analyzed 227 ddRAD tags (3829 SNP loci) across 42 samples. Molecular results strongly supported six Hypostomus genetic clusters/lineages, with the deepest divergence [~]1.25 million years ago in the early Pleistocene between a clade from the Upper Parana and Upper Sao Francisco river basins versus all other lineages. Consistent with the  Parana Capture Hypothesis, several lines of evidence supported mid-Pleistocene colonization and vicariant isolation of Hypostomus populations from an ancestral Upper Parana population, including: (1) significant phylogeographic structure, with predicted phylogenetic patterns, (2) higher Parana lineage diversity, (3) ancestral geographic locations reconstructed in the Parana basin, and (4) non-random interdrainage dispersal and vicariance events, indicating river captures primarily into the Tocantins and Upper Sao Francisco basins c. [~]220,000-145,500 years ago. Phylogeographic inference was complicated by lack of lineage monophyly across loci and lineages distributed in multiple basins, the latter of which lent support to the non-mutually exclusive  Frequent Interdrainage Dispersal Hypothesis. However, species tree and demographic modeling results suggested these were artefacts of incomplete sorting of alleles in large ancestral populations over a geologically recent timeframe of divergence. Qualitative and quantitative sensitivity analyses demonstrated that our downstream genetic results were robust to effects of varying ddRAD-seq assembly parameters, which heavily influenced the number of output loci. We predict that codistributed freshwater taxa in Central Brazil may not exhibit phylogeographic patterns similar to Hypostomus sp. 2 due to complex patterns of superimposed river capture events, or if smaller ancestral population sizes have allowed more complete lineage sorting in other taxa.

category: evolutionary biology


title: Age-dependent genetic architecture underlines similar heritability of body size in sticklebacks

abstract: Heritable variation in traits under natural selection is a prerequisite for evolutionary response. While it is recognised that trait heritability may vary spatially and temporally depending under which environmental conditions traits are expressed, less is known about the possibility that genetic variance contributing to the expected selection response in a given trait may vary at different stages of ontogeny. Specifically, whether different loci underlie the expression of a trait throughout development - thus providing an additional source of variation for selection to act on - is unclear. Here we show that the heritability (h2) of body size, an important life history trait, remains constant across ontogeny in a stickleback fish. Nevertheless, both analyses of quantitative trait loci (QTL) and genetic correlations across ages show that different chromosomes/loci contribute to this heritability in different ontogenic time-points. This suggests that body size can respond to selection at different stages of ontogeny but that this response is determined by different loci at different points of development. Hence, this illustrates the notion that diverse genetic architectures may underline similar (expected) phenotypic outcomes, and that similar selection pressures may lead to genetically heterogeneous responses depending on what life stage selection is acting on.


title: When good mutations go bad: how population size can change the direction of natural selection

abstract: Classical evolutionary theory holds that the efficiency, but not the direction, of natural selection depends on population size. In small populations, drift overwhelms selection, rendering all fitness-affecting mutations selectively neutral. Yet, beneficial mutations never become deleterious and deleterious mutations never become beneficial. Remarkably, several mutations, including in modifiers of recombination and mutation rate, have now been shown to be favored at some population sizes but disfavored at others, challenging established theory. Previously, we have designated this phenomenon sign inversion. Here we show that, unlike selected mutations in the classical framework, mutations susceptible to sign inversion confer both fitness costs and fitness benefits, that vary among their carriers. Furthermore, all such mutations can be classified based on whether their effects differ between or within mutant lineages. Using computer simulations, we demonstrate that both between-lineage and within-lineage variability can cause sign inversion and elucidate the common underlying mechanism. Our results confirm that variability in the sign of selective effects is necessary for sign inversion, which occurs because drift overwhelms selection on carriers bearing the cost and carriers enjoying the benefit at different population sizes.


title: Accurate assignment of disease liability to genetic variants using only population data

abstract:
PurposeThe growing size of public variant repositories prompted us to test the accuracy of predicting pathogenicity of DNA variants using population data alone.

MethodsUnder the a priori assumption that the ratio of the prevalence of variants in healthy and affected populations form two distinct distributions (pathogenic and benign), we used a Bayesian method to assign probability of a variant belonging to either distribution.

ResultsThe approach, termed BayPR, accurately parsed 300 of 313 expertly curated cystic fibrosis transmembrane conductance regulator (CFTR) variants: 284 of 296 pathogenic/likely pathogenic (P/LP) variants in one distribution and 16 of 17 benign/likely benign (B/LB) variants in another. BayPR produced an area under the receiver operating curve (AUC) of 0.99 for 103 functionally-confirmed missense CFTR variants, equal to or exceeding ten commonly used algorithms (AUC range: 0.54 to 0.99). Application of BayPR to expertly curated variants in eight genes associated with seven Mendelian conditions assigned [≥]80% disease-causing probability to 1,350 of 1,374 (98.3%) P/LP variants and [≤]20% to 22 of 23 (95.7%) B/LB variants.

ConclusionAgnostic to variant type or functional effect, BayPR provides probabilities of pathogenicity for DNA variants responsible for Mendelian disorders using only variant counts in affected and unaffected population samples.

category: genetics


title: Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior

abstract: Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce multivariate genomic-relatedness restricted maximum likelihood (MGREML) and provide estimates of the heritability of grey-matter volume in 74 regions of interest (ROIs) in the brain. We map genetic correlations between these ROIs and health-relevant behavioral outcomes including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs.


title: Unlocking inaccessible historical genomes preserved in formalin

abstract:
BackgroundMuseum specimens represent an unparalleled record of historical genomic data. However, the wide-spread practice of formalin preservation has thus far impeded genomic analysis of a large proportion of specimens. Limited DNA sequencing from formalin-preserved specimens has yielded low genomic coverage with unpredictable success. We set out to refine sample processing methods and to identify specimen characteristics predictive of sequencing success. With a set of taxonomically diverse specimens collected between 1936 and 2015 and ranging in preservation quality, we compared the efficacy of several end-to-end whole genome sequencing workflows alongside a k-mer-based trimming-free read alignment approach to maximize mapping of endogenous sequence.

ResultsWe recovered complete mitochondrial genomes and up to 3X nuclear genome coverage from formalin-fixed tissues. Hot alkaline lysis coupled with phenol-chloroform extraction out- performed proteinase K digestion in recovering DNA, while library preparation method had little impact on sequencing success. The strongest predictor of DNA yield was overall specimen condition, which additively interacts with preservation conditions to accelerate DNA degradation.

ConclusionsWe demonstrate a significant advance in capability beyond limited recovery of a small number of loci via PCR or target-capture sequencing. To facilitate strategic selection of suitable specimens for genomic sequencing, we present a decision-making framework that utilizes independent and non-destructive assessment criteria. Sequencing of formalin-fixed specimens will contribute to a greater understanding of temporal trends in genetic adaptation, including those associated with a changing climate. Our work enhances the value of museum collections worldwide by unlocking genomes of specimens that have been disregarded as a valid molecular resource.

category: genomics


title: Refining the evolutionary time machine: an assessment of whole genome amplification using single historical Daphnia eggs

abstract: Whole genome sequencing is instrumental for the study of genome variation in natural populations, delivering important knowledge on genomic modifications and potential targets of natural selection at the population level. Large dormant eggbanks of aquatic invertebrates such as the keystone herbivore Daphnia, a microcrustacean widespread in freshwater ecosystems, provide detailed sedimentary archives to study genomic processes over centuries. To overcome the problem of limited DNA amounts in single Daphnia dormant eggs, we developed an optimised workflow for whole genome amplification (WGA), yielding sufficient amounts of DNA for downstream whole genome sequencing of individual historical eggs, including polyploid lineages. We compare two WGA kits, applied to recently produced Daphnia magna dormant eggs from laboratory cultures, and to historical dormant eggs of Daphnia pulicaria collected from Arctic lake sediment between 10y and 300y old. Resulting genome coverage breadth in most samples was ~70%, including those from >100y old isolates. Sequence read distribution was highly correlated among samples amplified with the same kit, but less correlated between kits. Despite this, a high percentage of genomic positions with SNPs in one or more samples (maximum of 74% between kits, and 97% within kits) were recovered at a depth required for genotyping. As a by-product of sequencing we obtained 100% coverage of the mitochondrial genomes even from the oldest isolates (~300y). The mtDNA provides an additional source for evolutionary studies of these populations. We provide an optimised workflow for WGA followed by whole genome sequencing including steps to minimise exogenous DNA.


title: Mutant alleles differentially shape cattle complex traits and fitness

abstract: Classical mutant alleles (MAs), with large effects on phenotype, tend to be deleterious to traits and fitness. Is this the case for mutations with small effects? We infer MAs for 8 million sequence variants in 113k cattle and quantify the effects of MA on 37 complex traits. Heterozygosity for variants at genomic sites conserved across 100 vertebrates increase fertility, stature, and milk production, positively associating these traits with fitness. MAs decrease stature and fat and protein concentration in milk, but increase gestation length and somatic cell count in milk (the latter indicative of mastitis). However, the allele frequency of MAs that decrease fat and protein concentration and stature and increase gestation length and somatic cell count is lower than the allele frequency of MAs with the opposite effect. These results suggest bias in the direction of effect of mutation (e.g. towards reduced protein in milk), but selection operating to reduce the frequency of these MAs. Taken together, our results imply two classes of genomic sites subject to long-term selection: sites conserved across vertebrates show hybrid vigour while sites subject to less long-term selection show a bias in mutation towards alleles that are selected against.


title: Systematic discovery and perturbation of regulatory genes in human T cells reveals the architecture of immune networks

abstract:
Complex gene regulatory networks ensure that important genes are expressed at precise levels. When gene expression is sufficiently perturbed it can lead to disease. To understand how gene expression disruptions percolate through a network, we must first map connections between regulatory genes and their downstream targets. However, we lack comprehensive knowledge of the upstream regulators of most genes. Here we developed an approach for systematic discovery of upstream regulators of critical immune factors - IL2RA, IL-2, and CTLA4 - in primary human T cells. Then, we mapped the network of these regulators target genes and enhancers using CRISPR perturbations, RNA-Seq, and ATAC-Seq. These regulators form densely interconnected networks with extensive feedback loops. Furthermore, this network is highly enriched for immune-associated disease variants and genes. These results provide insight into how immune-associated disease genes are regulated in T cells and broader principles about the structure of human gene regulatory networks.

HighlightsO_LIA systematic approach to identify upstream regulators of key immune genes in primary human cells
C_LIO_LIComprehensive RNA-Seq and ATAC-Seq perturbation maps after KO of individual discovered regulators
C_LIO_LIAnalysis uncovers a highly interconnected regulatory network of enhancers and genes in T cells
C_LIO_LIThis network is highly enriched for immune disease variants and genes shedding light on the trans-regulatory connections among key immune genes in health and disease
C_LI


title: Appetitive learning relies on octopamine and dopamine in ants

abstract: Associative learning relies on the detection of coincidence between a stimulus and a reward or punishment. In the insect brain, this process is thought to be carried out in the mushroom bodies under control of octopaminergic and dopaminergic neurons. It was assumed that appetitive learning is governed by octopaminergic neurons, while dopamine is required for aversive learning. This view has been recently challenged: Both neurotransmitters seem to be involved in both types of memory in bees and flies. Here, we test which neurotransmitters are required for appetitive learning in ants. We trained Lasius niger ant workers to discriminate two mixtures of linear hydrocarbons and associate one of them with a sucrose reward. We analysed the behaviour of the trained ants using machine learning and found that they preferred the rewarded odour over the other, a preference that was stable for at least 24 hours. We then treated the ants before learning with either epinastine, an octopamine receptor blocker, or with flupentixol, a dopamine receptor blocker. Ants with blocked octopamine receptors did not remember the rewarded odour. Octopamine signalling is thus necessary for the formation of appetitive memory. In contrast, ants with blocked dopamine receptors initially learned the rewarded odour but failed to retrieve this memory 24 hours later. Dopamine is thus required for long-term memory consolidation during appetitive conditioning, independent of short-term memory formation. Our results show that appetitive learning depends on both octopamine and dopamine signalling in ants.

category: animal behavior and cognition


title: Wood ants express uncertainty when engaging with magnetic cues for directional guidance

abstract: Wood ants were trained indoors to follow a route in a chosen magnetic direction from the centre of a small, circular arena to find a drop of sucrose at the edge. The arena, surrounded by a white cylindrical wall, was in the centre of a 3D coil system that generated an inclined Earth strength magnetic field in any horizontal direction. Between trials, the chosen magnetic training direction was rotated to a new orientation. Tests were given without food and with fresh or reversed paper on the floor of the arena. In a significant number of tests, ants left the centre facing the goal, or in the opposite direction, but they mostly failed to reach the goal. Tests given early in the day, before any training, show that ants remember the magnetic route direction overnight. On some training trials, the position of the sucrose was also indicated by a black stripe. Not uncommonly, ants first moved in the opposite direction to the stripe before switching to the correct direction. Travel away from the reward seems to express the ants uncertainty about the correct path to take. Tests show that this uncertainty may stem from competing directional cues linked to the room, suggesting that ants are reluctant to rely on magnetic information alone. We conclude that ants can remember a route direction defined by an Earth-strength magnetic field and that they express any uncertainty about the correct direction by moving for a stretch in the opposite direction. In a second experiment, an upright and an inverted triangle were fixed 90{degrees} from each other to the inside of the cylinder. Sucrose was placed beneath one of the triangles, dependent on the direction of the magnetic field. Ants failed to master this task and to approach the magnetically cued triangle. Instead, they preferred to approach the upright triangle. The ants were again uncertain of the correct direction and expressed this uncertainty through paths that had segments directed towards both the inverted and the upright triangles.


title: Vocal correlates of arousal in bottlenose dolphins (Tursiops spp.) in human care

abstract: Human-controlled regimes can entrain behavioural responses and may impact animal welfare. Therefore, understanding the impact of schedules on animal behaviour can be a valuable tool to improve welfare, however information on overnight behaviour and behaviour in the absence of husbandry staff remains rare. Bottlenose dolphins (Tursiops spp.) are highly social marine mammals and the most common cetacean found in captivity. They communicate using frequency modulated signature whistles which are individually distinctive and used as a contact call. We investigated the vocal behaviour of ten dolphins housed in three social groups at uShaka Sea World dolphinarium to determine how acoustic behavioural patterns link to dolphinarium routines. Investigation focused on overnight behaviour, housing decisions, weekly patterns, and transitional periods between presence and absence of husbandry staff. Recordings were made from 17h00 - 07h00 over 24 nights, spanning May to August 2018. Whistle production rate decreased soon after husbandry staff left the facility, was low over night, and increased upon arrival. Results indicated elevate arousal states associated with the morning arrival and presence of husbandry staff and heightened excitement associated with feeding. Housing in pool configurations which limited visual contact between certain groups were characterised by lower vocal production rates. Production of signature whistles was greater over the weekends compared to weekdays however total whistle production did not differ between weekends and weekdays. Heightened arousal associated with staff arrival was reflected in the structural characteristics of signature whistles, particularly maximum frequency, frequency range and number of whistle loops. Overall, these results revealed a link between scheduled activity and associated behavioural responses, which can be used as a baseline for future welfare monitoring where changes in normal behaviour may reflect shifts in welfare state.


title: Identifying Upper Airway and Evaluating Adenoid in Lateral Cephalometric Radiographs of Pediatric Patients Using Image-based Deep Learning Technique

abstract:
PurposeAdenotonsillar hypertrophy is considered as one of the primary causes of pediatric obstructive sleep apnea. In clinical practice, pediatric patients with potential obstructive apnea should undergo assessment of upper airway obstruction and adenotonsillar size. As lack of well-trained physicians in China, large numbers of such patients could not be accurately evaluated in time. We attempted to find a better way to assess upper airway obstruction.

MethodsWe developed a computational method which may allow clinicians to trace upper airway obstruction. We utilized a Detectron2 Mask R-CNN architecture that was pretrained on ImageNet-1k dataset. We then trained it on our COCO dataset using transfer learning for segmentations of upper airway and related key structures. With the instance segmentations, we utilized a tracing algorithm developed by our own to sketch the contours of key segments. At the end, our system would use the traced landmarks to calculate the targeted clinical data.

ResultsWe validated the effective-ness of the algorithm in two steps. First, we used a validation set (COCO dataset) to evaluate the segmentation performance of our system. Our system achieved a mean segmentation AP of 61.30, with airway segmentation AP of 55.64 and cranial base segmentation AP of 66.96. In addition, the AP50 was 99.49 and AP75 was 73.62. Second,we analyzed the data from our system and experts using a single rater, absolute-agreement, 2-way mixed-effects model, and got ICC value of 0.73 with 95% confident interval = 0.63-0.81.

ConclusionsIn this study, we created a deep-learning based system to help clinicians evaluate upper airway in lateral cephalometric radiographs which we believe could improve clinical practice. With the evolving of technology, our system would become more integrated into medical care of OSA, freeing the clinical practitioners from repetitive tasks and enabling them to concentrate on improved patient care.

category: bioengineering


title: AIE nanoparticles camouflaged with tumor cell-derived exosomes for NIR-II imaging-guided photothermal therapy

abstract: Nanoparticles (NPs) assisted photothermal therapy (PTT) is a promising cancer treatment modality and has attracted the attention of the scientific mainstream. However, developing NPs that exhibit efficient optical properties and specific tumor targeting capability simultaneously is difficult. Herein, we develop hybrid nanovesicles consisting of tumor cell-derived exosomes (EXO) and organic aggregation-induced emission (AIE) nanoparticles (TT3-oCB NP@EXOs) with enhanced second near-infrared (NIR-II, 900-1700 nm) fluorescence property and PTT functionality. Compared with TT3-oCB NPs, TT3-oCB NP@EXOs exhibit excellent biocompatibility, specific targeting ability in vitro, homing to homologous tumors in vivo, and prolonged circulation time. Furthermore, TT3-oCB NP@EXOs were utilized as biomimetic NPs for NIR-II fluorescence imaging-guided PTT of tumors, due to their high and stable photothermal conversion capacity under 808 nm irradiation. Therefore, the tumor cell-derived EXO/AIE NP hybrid nanovesicles may provide an alternative artificial targeting strategy for improving tumor diagnosis and PTT.


title: Programmable and Contractile Materials Through Cell Encapsulation in Fibrous Hydrogel Assemblies

abstract: The natural extracellular matrix (ECM) within tissues is physically contracted and remodeled by cells, allowing the collective shaping of functional tissue architectures. Synthetic materials that facilitate self-assembly similar to natural ECM are needed for cell culture, tissue engineering, and in vitro models of development and disease. To address this need, we develop fibrous hydrogel assemblies that are stabilized with photocrosslinking and display fiber density dependent strain responsive properties (strain-stiffening, alignment). Encapsulated mesenchymal stromal cells locally contract low fiber density assemblies, resulting in macroscopic volumetric changes with increased cell densities and moduli. Due to properties such as shear-thinning and self-healing, assemblies can be processed into microtissues with aligned ECM deposition or through extrusion bioprinting and photopatterning to fabricate constructs with programmed shape changes due to cell contraction. These materials provide a synthetic approach to mimic features of natural ECM, which can now be processed for applications in biofabrication and tissue engineering.


title: Scalable Batch Fabrication of Ultrathin Flexible Neural Probes using Bioresorbable Silk Layer

abstract: Flexible deep brain probes have been the focus of many research works and aims at achieving better compliance with the surrounding brain tissue while maintaining minimal rejection. Strategies have been explored to find the best way to implant a flexible probe in the brain, while maintaining its flexibility once positioned in the cortex. Here, we present a novel and versatile scalable batch fabrication approach to deliver ultra-thin and flexible penetrating neural probe consisting of a silk-parylene bilayer. The biodegradable silk layer provides a temporary and programmable stiffener to ensure ease of insertion of the ultrathin parylene-based flexible devices. The innovative and yet robust batch fabrication technology allows complete design freedom of the neural probe in terms of materials, size, shape and thickness. These results provide a novel technological solution for implanting ultra-flexible and ultrathin devices, which possesses great potential for brain research.


title: Perfecting and extending the near-infrared biological window

abstract: In vivo fluorescence imaging in the second near-infrared window (NIR-II) has been considered as a promising technique for visualizing the mammals. However, the definition of the NIR-II region and the mechanism accounting for the excellent performance still need to be perfected. Herein, we simulated bioimaging in the NIR spectral range (to 2340 nm), confirmed the positive contribution of moderate light absorption by water in intravital imaging and perfected the NIR-II window as 900-1880 nm, where the 1400-1500 nm was defined as NIR-IIx region and the 1700-1880 nm was defined as NIR-IIc region, respectively. Moreover, the 2080-2340 nm was newly proposed as the third near-infrared (NIR-III) window, which was believed to provide the best imaging quality. The wide-field fluorescence microscopy in brain, in addition, was performed around NIR-IIx region with excellent optical sectioning strength and the largest imaging depth of in vivo NIR-II fluorescence microscopy to date. We also proposed 1400 nm long-pass detection in off-peak NIR-II imaging whose profits exceeded those of NIR-IIb imaging, using bright fluorophores with short peak emission wavelength.


title: Fibrin Prestress Due to Platelet Aggregation and Contraction Increases Clot Stiffness

abstract: Efficient haemorrhagic control is attained through the formation of strong and stable blood clots at the site of injury. Although it is known that platelet-driven contraction can dramatically influence clot stiffness, the underlying mechanisms by which platelets assist fibrin networks in resisting external loads are not understood. In this study, we delineate the contribution of platelet-fibrin interactions to clot tensile mechanics using a combination of new mechanical measurements, image analysis, and structural mechanics simulation. Based on uniaxial tensile test data using custom-made microtensometer, and fluorescence microscopy of platelet aggregation and platelet-fibrin interactions, we show that integrin-mediated platelet aggregation and actomyosin-driven platelet contraction synergistically increase the elastic modulus of the clots. We demonstrate that the mechanical and geometric response of an active contraction model of platelet aggregates compacting vicinal fibrin is consistent with the experimental data. The model suggests that platelet contraction induces prestress in fibrin fibres, and increases the effective stiffness in both crosslinked and non-crosslinked clots. Our results provide evidence for fibrin compaction at discrete nodes as a major determinant of mechanical response to applied loads.


title: Nanoconfinement of Microvilli Alters Gene Expression and Boosts T cell Activation

abstract: T cells sense and respond to their local environment at the nanoscale by forming small actin-rich protrusions, called microvilli, which play critical roles in signaling and antigen recognition, particularly at the interface with the antigen presenting cells. However, the mechanisms by which microvilli contribute to cell signaling and activation is largely unknown. Here, we present a tunable engineered system that promotes microvilli formation and T cell signaling via physical stimuli. We discovered that nanoporous surfaces favored microvilli formation, and markedly altered gene expression in T cells and promoted their activation. Mechanistically, confinement of microvilli inside of nanopores leads to size-dependent sorting of membrane-anchored proteins, specifically segregating CD45 phosphatases and T cell receptors (TCR) from the tip of the protrusions when microvilli are confined in 200 nm pores, but not in 400 nm pores. Consequently, formation of TCR nanoclustered hotspots within 200 nm pores, allows sustained and augmented signaling that prompts T cell activation even in the absence of TCR agonists. The synergistic combination of mechanical and biochemical signals on porous surfaces presents a straightforward strategy to investigate the role of microvilli in T cell signaling as well as to boost T cell activation and expansion for application in the growing field of adoptive immunotherapy.


title: MS2DeepScore - a novel deep learning similarity measure for mass fragmentation spectrum comparisons

abstract:
Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are considered characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics.

Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of >100,000 mass spectra of about 15,000 unique known compounds, MS2DeepScore learns to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the models prediction uncertainty. On 3,600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and predicts Tanimoto scores with a root mean squared error of about 0.15. The prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. We demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity metrics have great potential for a range of metabolomics data processing pipelines.

category: bioinformatics


title: Connecting MHC-I-binding motifs with HLA alleles via deep learning

abstract: The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performance on binding affinity. However, the decisive MHC residues and their relation to the selection of binding peptides are still unrevealed. Here, we connected HLA alleles with binding motifs via our deep learning-based framework, MHCfovea. MHCfovea expanded the knowledge of MHC-I-binding motifs from 150 to 13,008 alleles. After clustering N-terminal and C-terminal sub-motifs on both observed and unobserved alleles, MHCfovea calculated the hyper-motifs and the corresponding allele signatures on the important positions to disclose the relation between binding motifs and MHC-I sequences. MHCfovea delivered 32 pairs of hyper-motifs and allele signatures (HLA-A: 13, HLA-B: 12, and HLA-C: 7). The paired hyper-motifs and allele signatures disclosed the critical polymorphic residues that determine the binding preference, which are believed to be valuable for antigen discovery and vaccine design when allele specificity is concerned.


title: ChIP-AP, An Integrated ChIP-Seq Analysis Pipeline

abstract: ChIP-Seq is a technique used to analyse protein-DNA interactions. The protein-DNA complex is pulled down using a protein antibody, after which sequencing and analysis of the bound DNA fragments is performed. A key bioinformatics analysis step is "peak" calling - identifying regions of enrichment. Benchmarking studies have consistently shown that no optimal peak caller exists. Peak callers have distinct selectivity and specificity characteristics which are often not additive and seldom completely overlap in many scenarios. In the absence of a universal peak caller, we rationalized one ought to utilize multiple peak-callers to 1) gauge peak confidence as determined through detection by multiple algorithms, and 2) more thoroughly survey the protein-bound landscape by capturing peaks not detected by individual peak callers owing to algorithmic limitations and biases. We therefore developed an integrated ChIP-Seq Analysis Pipeline (ChIP-AP) which performs all analysis steps from raw fastq files to final result, and utilizes four commonly used peak callers to more thoroughly and comprehensively analyse datasets. Results are integrated and presented in a single file enabling users to apply selectivity and sensitivity thresholds to select the consensus peak set, the union peak set, or any sub-set in-between to more confidently and comprehensively explore the protein-bound landscape. (https://github.com/JSuryatenggara/ChIP-AP).


title: The power of universal contextualised protein embeddings in cross-species protein function prediction

abstract:
Computationally annotating proteins with a molecular function is a difficult problem that is made even harder due to the limited amount of available labelled protein training data. A recently published supervised molecular function predicting model partly circumvents this limitation by making its predictions based on the universal (i.e. task-agnostic) contextualised protein embeddings from the deep pre-trained unsupervised protein language model SeqVec. SeqVec embeddings incorporate contextual information of amino acids, thereby modelling the underlying principles of protein sequences insensitive to the context of species.

We applied the existing SeqVec-based molecular function prediction model in a transfer learning task by training the model on annotated protein sequences of one training species and making predictions on the proteins of several test species with varying evolutionary distance. We show that this approach successfully generalises knowledge about protein function from one eukaryotic species to various other species, proving itself an effective method for molecular function prediction in inadequately annotated species from understudied taxonomic kingdoms. Furthermore, we submitted the performance of our SeqVec-based prediction models to detailed characterisation, first to advance the understanding of protein language models and second to determine areas of improvement.

Author summaryProteins are diverse molecules that regulate all processes in biology. The field of synthetic biology aims to understand these protein functions to solve problems in medicine, manufacturing, and agriculture. Unfortunately, for many proteins only their amino acid sequence is known whereas their function remains unknown. Only a few species have been well-studied such as mouse, human and yeast. Hence, we need to increase knowledge on protein functions. Doing so is, however, complicated as determining protein functions experimentally is time-consuming, expensive, and technically limited. Computationally predicting protein functions offers a faster and more scalable approach but is hampered as it requires much data to design accurate function prediction algorithms. Here, we show that it is possible to computationally generalize knowledge on protein function from one well-studied training species to another test species. Additionally, we show that the quality of these protein function predictions depends on how structurally similar the proteins are between the species. Advantageously, the predictors require only the annotations of proteins from the training species and mere amino acid sequences of test species which may particularly benefit the function prediction of species from understudied taxonomic kingdoms such as the Plantae, Protozoa and Chromista.


title: Enhanced longitudinal differential expression detection in proteomics with robust reproducibility optimization regression

abstract: Quantitative proteomics has matured into an established tool and longitudinal proteomic experiments have begun to emerge. However, no effective, simple-to-use differential expression method for longitudinal proteomics data has been released. Typically, such data is noisy, contains missing values, has only few time points and biological replicates. To address this need, we provide a comprehensive evaluation of several existing differential expression methods for high-throughput longitudinal omics data and introduce a new method, Robust longitudinal Differential Expression (RolDE). The methods were evaluated using nearly 2000 semi-simulated spike-in proteomic datasets and a large experimental dataset. The RolDE method performed overall best; it was most tolerant to missing values, displayed good reproducibility and was the top method in ranking the results in a biologically meaningful way. Furthermore, contrary to many approaches, the open source RolDE does not require prior knowledge concerning the types of differences searched, but can easily be applied even by non-experienced users.


title: Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis

abstract: To provide a better understanding of dementia at the molecular level, this study aimed to identify the genes and key pathways associated with dementia by using integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing dataset GSE153960 derived from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between patients with dementia and healthy controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed, analyzed and visualized, with which the hub genes miRNAs and TFs nodes were screened out. Finally, validation of hub genes was performed by using receiver operating characteristic curve (ROC) analysis. A total of 948 DEGs were screened out, among which 475 genes were up regulated; while 473 were down regulated. Functional enrichment analyses indicated that DEGs were mainly involved in defense response, ion transport, neutrophil degranulation and neuronal system. The hub genes (CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B and HSPA12B) were identified from PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. We identified a series of key genes along with the pathways that were most closely related with dementia initiation and progression. Our results provide a more detailed molecular mechanism for the advancement of dementia, shedding light on the potential biomarkers and therapeutic targets.


title: The Drosophila DCP2 is evolutionarily conserved in sequence and structure : insights from in silico studies of DmDCP2 orthologs and paralogs

abstract: The mRNA decapping proteins (DCPs) function to hydrolyze the 7-methylguanosine cap at the 5 end of mRNAs thereby, exposing the transcript for degradation by the exonuclease(s) and hence, play a pioneering role in the mRNA decay pathway. In Drosophila melanogaster, the mRNA decapping protein 2 (DCP2) is the only catalytically active mRNA decapping enzyme present. Despite its presence being reported across diverse species in the phylogenetic tree, a quantitative approach to the index of its conservation in terms of its sequence has not been reported so far. With structural and mechanistic insights being explored in the yeasts, the insect DCP2 has never been explored in the perspectives of structure and the indices of the conservation of its sequence and/or structure vis-a-vis topological facets. Being an evolutionarily conserved protein, the present endeavor aimed at deciphering the evolutionary relationship(s) and the pattern of conservation of the sequence of DCP2 across the phylogenetic tree as well as in sibling species of D. melanogaster through a semi-quantitative approach relying on multiple sequence alignment and analyses of percentage identity matrices. Since NUDIX proteins are functionally diverse, an attempt to identify the other NUDIX proteins (or, DCP2 paralogs) in D. melanogaster and compare and align their structural features with that of DCP2 through in silico approaches was endeavored in parallel. Our observations provide quantitative and structural bases for the observed evolutionary conservation of DCP2 across the diverse phyla and also, identify and reinforce the structural conservation of the NUDIX family in D. melanogaster.


title: Exogene: A performant workflow for detecting viral integrations from paired-end next-generation sequencing data

abstract: The integration of viruses into the human genome is known to be associated with tumorigenesis in many cancers, but the accurate detection of integration breakpoints from short read sequencing data is made difficult by human-viral homologies, viral genome heterogeneity, coverage limitations, and other factors. To address this, we present Exogene, a sensitive and efficient workflow for detecting viral integrations from paired-end next generation sequencing data. Exogenes read filtering and breakpoint detection strategies yield integration coordinates that are highly concordant with those found in long read validation sets. We demonstrate this concordance across 6 TCGA Hepatocellular carcinoma (HCC) tumor samples, identifying integrations of hepatitis B virus that are validated by long reads. Additionally, we applied Exogene to targeted capture data from 426 previously studied HCC samples, achieving 98.9% concordance with existing methods and identifying 238 high-confidence integrations that were not previously reported. Exogene is applicable to multiple types of paired-end sequence data, including genome, exome, RNA-Seq or targeted capture.


title: On the Driver of Blood Circulation Beyond the Heart

abstract: The heart is widely acknowledged as the unique driver of blood circulation. Recently, we discovered a flow-driving mechanism that can operate without imposed pressure, using infrared (IR) energy to propel flow. We considered the possibility that, by exploiting this mechanism, blood vessels, themselves, could propel flow. We verified the existence of this driving mechanism by using a three-day-old chick-embryo model. When the heart was stopped, blood continued to flow, albeit at a lower velocity. When IR was introduced, flow increased, by [~]300%. When IR energy was diminished under otherwise physiological conditions, blood failed to flow. Hence, this IR-dependent, vessel-based flow-driving mechanism may indeed operate in the circulatory system, complementing the action of the heart.

category: biophysics


title: Surface residues and non-additive interactions stabilize a consensus homeodomain protein

abstract:
Despite the widely reported success of consensus design in producing highly stabilized proteins, little is known about the physical mechanisms underlying this stabilization. Here we explore the potential sources of stabilization by performing a systematic analysis of the 29 substitutions that we previously found to collectively stabilize a consensus homeodomain compared to an extant homeodomain. By separately introducing groups of consensus substitutions that alter or preserve charge state, occur at varying degrees of residue burial, and occur at positions of varying degrees of conservation, we determine the extent to which these three features contribute to the consensus stability enhancement. Surprisingly, we find that the largest total contribution to stability comes from consensus substitutions on the protein surface and that the largest per-substitution contributions come from substitutions that maintain charge state, suggesting that although consensus proteins are often enriched in charged residues, consensus stabilization does not result primarily from charge-charge interactions. Although consensus substitutions at strongly conserved positions also contribute disproportionately to stabilization, significant stabilization is also contributed from substitutions at weakly conserved positions. Furthermore, we find that identical consensus substitutions show larger stabilizing effects when introduced into the consensus background than when introduced into an extant homeodomain, indicating that synergistic, stabilizing interactions among the consensus residues contribute to consensus stability enhancement of the homeodomain.

Significance StatementProteins composed of consensus sequences from multiple sequence alignments are often more stable than extant proteins used to create them. Often about half the residues in a consensus protein differ from those of extant proteins. The contributions of these differences to stability are unknown. Here we substitute groups of residues with different properties (conservation, charge variation, solvent accessibility) to determine which substitutions lead to consensus stabilization. We find that surface and charge-conserving substitutions contribute to stability, that weakly-conserved substitutions make a significant collective contribution to stability, and that there is a significant non-additive contribution to stability in the consensus background. These results provide insights to the sequence origins of consensus stabilization and the evolutionary constraints that determine protein sequences.


title: Deformation of membrane vesicles due to chiral surface proteins

abstract:
Chiral, rod-like molecules can self-assemble into cylindrical membrane tubules and helical ribbons. They have been successfully modeled using the theory of chiral nematics. Models have also predicted the role of chiral lipids in forming nanometer-sized membrane buds in the cell. However, in most theoretical studies, the membrane shapes are considered fixed (cylinder, sphere, saddle, etc.), and their optimum radius of curvatures are found variationally by minimizing the energy of the composite system consisting of membrane and chiral nematics. Numerical simulations have only recently started to consider membrane deformation and chiral orientation simultaneously. Here we examine how deformable, closed membrane vesicles and chiral nematic rods mutually influence each others shape and orientation, respectively, using Monte-Carlo (MC) simulation on a closed triangulated surface. For this, we adopt a discrete form of chiral interaction between rods, originally proposed by Van der Meer et al. (1976) for off-lattice simulations. In our simulation, both conical and short cylindrical tubules emerge, depending on the strength of the chiral interaction and the intrinsic chirality of the molecules. We show that the Helfrich-Prost term, which couple nematic tilt with local membrane curvature in continuum models, can account for most of the observations in the simulation. At higher chirality, our theory also predicts chiral tweed phase on cones, with varying bandwidths.

PACS numbers: PACS : 87.16.-b, 87.15.Aa, 81.40.Jj, 87.15.Rn