title: Interferon induction and not replication interference mainly determines anti-influenza virus activity of defective interfering particles

abstract:
Defective interfering (DI) RNAs arise during influenza virus replication, can be packaged into particles (DIPs) and suppress spread of wildtype (WT) virus. However, the molecular signatures of DI RNAs and the mechanism underlying antiviral activity are incompletely understood. Here, we show that any central deletion is sufficient to convert a viral RNA into a DI RNA and that antiviral activity of DIPs is inversely correlated with DI RNA length when induction of the interferon (IFN) system is disfavored. When induction of the IFN system was allowed, it was found to be the major contributor to DIP antiviral activity. Finally, while both DIPs and influenza virus triggered expression of IFN-stimulated genes (ISG) only virus stimulated robust expression of IFN. These results suggest a key role of innate immune activation in DIP antiviral activity and point towards previously unappreciated differences in DIP- and influenza virus-mediated activation of the effector functions of the IFN system.

ImportanceDefective interfering (DI) RNAs naturally arise during RNA virus infection. They can be packaged into defective interfering particles (DIPs) and exert antiviral activity by suppressing viral genome replication and inducing the interferon (IFN) system. However, inhibition of influenza virus infection by DI RNAs has been incompletely understood. Here, we show that induction of the IFN system and not suppression of genome replication is the major determinant of DIP antiviral activity. Moreover, we demonstrate that DIPs induce IFN-stimulated genes (ISG) but not IFN with high efficiency. Our results reveal unexpected major differences in influenza virus and DIP activation of the IFN system, a key barrier against viral infection, and provide insights into how to design DIPs for antiviral therapy.

category: molecular biology


title: Fractional-order Approach to Modeling and Characterizing the Complex and Frequency-dependent Apparent Arterial Compliance: In Human and Animal Validation

abstract: Recently, experimental and theoretical studies have revealed the potential of fractional calculus to represent viscoelastic blood vessel and arterial biomechanical properties. This paper presents five fractional-order models to describe the dynamic relationship between aortic blood pressure and volume, representing the apparent vascular compliance. The proposed model employs fractional-order capacitor element (FOC) to lump the complex and frequency dependence characteristics of arterial compliance. FOC combines both resistive and capacitive properties, which the fractional differentiation order, , can control. The proposed representations have been compared with generalized integer-order models of arterial compliance. All structures have been validated using different aortic pressure and flow rate waveforms collected from various human and animal species such as pigs and dogs. The results demonstrate that the fractional-order scheme can reconstruct the overall dynamic of the complex and frequency-dependent apparent compliance dynamic and reduce the complexity. The physiological relevance of the proposed models parameters was assessed by evaluating the variance-based global sensitivity analysis. Moreover, the simplest fractional-order representation has been embed in a global arterial lumped parameter representation to develop a novel fractional-order modified arterial Windkessel. The introduced arterial model has been validated by applying real human and animal hemodynamic data and shows an accurate reconstruction of the proximal blood pressure. The novel proposed paradigm confers a potential to be adopted in clinical practice and basic cardiovascular mechanics research.

category: bioengineering


title: Sensing Local Field Potentials with a Directional and Scalable Depth Array: DISC

abstract: A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enabling directional sensitivity and scalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting.


title: Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC array


title: Sensing Local Field Potentials with a Directional and Scalable Depth Electrode Array


title: DeNovoCNN: A deep learning approach to de novo variant calling in next generation sequencing data

abstract: De novo mutations (DNMs) are an important cause of genetic disorders. The accurate identification of DNMs from sequencing data is therefore fundamental to rare disease research and diagnostics. Unfortunately, identifying reliable DNMs remains a major challenge due to sequence errors, uneven coverage, and mapping artifacts. Here, we developed a deep convolutional neural network (CNN) DNM caller (DeNovoCNN), that encodes alignment of sequence reads for a trio as 160x164 resolution images. DeNovoCNN was trained on DNMs of whole exome sequencing (WES) of 2003 trios achieving on average 99.2% recall and 93.8% precision. We find that DeNovoCNN has increased recall/sensitivity and precision compared to existing de novo calling approaches (GATK, DeNovoGear, Samtools) based on the Genome in a Bottle reference dataset. Sanger validations of DNMs called in both exome and genome datasets confirm that DeNovoCNN outperforms existing methods. Most importantly, we show that DeNovoCNN is robust against different exome sequencing and analyses approaches, thereby allowing it to be applied on other datasets. DeNovoCNN is freely available and can be run on existing alignment (BAM/CRAM) and variant calling (VCF) files from WES and WGS without a need for variant recalling.

category: bioinformatics


title: ProMetheusDB: an in-depth analysis of the high-quality human methyl-proteome

abstract: Protein Arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumour development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analysed with a machine learning-based tool doublets and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein:RNA interactions and suggest a role in rewiring protein:protein interactions, for which we provide experimental evidence for a representative case (i.e. NONO:PSPC1). Upon intersecting our R-methyl-sites dataset with a phosphosites dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of hmSILAC to identify unconventional methylated residues and successfully identified novel histone methylation marks on Serine 28 and Threonine 32 of H3.


title: Integrated de novo Gene Prediction and Peptide Assembly of Metagenomic Sequencing Data

abstract: Metagenomics is the study of all genomic content presented in given microbial communities. Metagenomic functional analysis aims to quantify protein families and reconstruct metabolic pathways from the metagenome. It plays a central role in understanding the interaction between the microbial community and its host or environment. De novo functional analysis, which allows the discovery of novel protein families, remains challenging for high-complexity communities. There are currently three main approaches for recovering novel genes or proteins: de novo nucleotide assembly, gene calling, and peptide assembly. Unfortunately, their informational connection and dependency have been overlooked, and each has been formulated as an independent problem. In this work, we develop a sophisticated workflow called integrated Metagenomic Protein Predictor (iMPP), which leverages the informational dependencies for better de novo functional analysis. iMPP contains three novel modules: a hybrid assembly graph generation module, a graph-based gene calling module, and a peptide assembly-based refinement module. iMPP significantly improved the existing gene calling sensitivity on unassembled fragmented reads, achieving a 92% - 97% recall rate at a high precision level (>90%). iMPP further allowed for more sensitive and accurate peptide assembly, recovering more reference proteins and delivering more hypothetical protein sequences. The high performance of iMPP can provide a more comprehensive and unbiased view of the microbial communities under investigation. iMPP is freely available from https://github.com/Sirisha-t/iMPP.


title: A Methodology for Vertical Translation Between Molecular and Organismal Level in Biological Feedback Loops

abstract:
Feedback loops are among the primary network motifs in living organisms, ensuring survival via homeostatic control of key metabolites and physical properties. However, from a scientific perspective, their characterization is unsatisfactory since the usual modelling methodology is incompatible with the physiological and biochemical basis of metabolic networks. Therefore, any "vertical translation", i.e. the study of the correspondence between molecular and organismal levels of causality, is difficult and in most cases impossible.

As a viable solution, we demonstrate an alternative modelling platform for biological feedback loops that is based on key biochemical principles, including mass action law, enzyme kinetics, binding of mediators to transporters and receptors, and basic pharmacological properties. Subsequently, we show how this framework can be used for translating from molecular to systems-level behaviour.

Basic elements of the proposed modelling platform include Michaelis-Menten kinetics defining nonlinear dependence of the output y(t) on an input signal x(t) with the Hill-Langmuir equation y(t) = G * x(t)n / (D + x(t)n), non-competitive inhibition for linking stimulatory and inhibitory inputs with y(t) = G + x1(t) / ((D + x1(t) * (1 + x2(t) / KI)) and processing structures for distribution and elimination.

Depending on the structure of the feedback loop, its equifinal (steady-state) behaviour can be solved in form of polynomials, with a quadratic equation for the simplest case with one feedback loop and a Hill exponent of 1, and higher-grade polynomials for additional feedback loops and/or integer Hill exponents > 1. As a companion to the analytical solution, a flexible class library (CyberUnits) facilitates computer simulations for studying the transitional behaviour of the feedback loop.

Unlike other modelling strategies in biocybernetics and systems biology, this platform allows for straightforward translation from the statistical properties of single molecules on a "microscopic" level to the behaviour of the whole feedback loop on an organismal "macroscopic" level. An example is the Michaelis constant D, which is equivalent to (k-1 + k2) / k1, where k1, k-1 and k2 denote the rate constants for the association and dissociation of the enzyme-substrate or receptor-hormone complex, respectively. From the perspective of a single molecule the rate constants represent the probability (per unit time) that the corresponding reaction will happen in the subsequent time interval. Therefore 1/k represents the mean lifetime of the complex. Very similar considerations apply to the other described constants of the feedback loop.

In summary, this modelling technique renders the translation from a molecular level to a systems perspective possible. In addition to providing new insights into the physiology of biological feedback loops, it may be a valuable tool for multiple disciplines of biomedical research, including drug design, molecular genetics and investigations on the effects of endocrine disruptors.

category: systems biology


title: Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization

abstract: Quantifying the population sizes of distinct neuron types in different anatomical regions is an essential step towards establishing a brain cell census. Although estimates exist for the total neuronal populations in different species, the number and definition of each specific neuron type are still intensively investigated. Hippocampome.org is an open-source knowledge base with morphological, physiological, and molecular information for 122 neuron types in the rodent hippocampal formation. While such framework identifies all known neuron types in this system, their relative abundances remain largely unknown. This work quantitatively estimates the counts of all Hippocampome.org neuron types by literature mining and numerical optimization. We report the number of neurons in each type identified by main neurotransmitter (glutamate or GABA) and axonal-dendritic patterns throughout 26 subregions and layers of the dentate gyrus, Ammons horn, subiculum, and entorhinal cortex. We produce by sensitivity analysis reliable numerical ranges for each type and summarize the amounts across broad neuronal families defined by biomarkers expression and firing dynamics. Study of density distributions indicates that the number of dendritic-targeting interneurons, but not of other neuronal classes, is independent of anatomical volumes. All extracted values, experimental evidence, and related software code are released on Hippocampome.org.

category: neuroscience


title: Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation

abstract:
BackgroundTranscranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer.

ObjectiveTo develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region.

MethodsWe designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand.

ResultsThe transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum.

ConclusionThe developed mTMS system enables electronically targeted brain stimulation within a cortical region.


title: Real-time audio processing of real-life soundscapes for EEG analysis: ERPs based on natural sound onsets

abstract: With smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS) and power spectral density (PSD) on smartphone. In this paper, we evaluate these apps by computing event-related potentials (ERPs) evoked by everyday sounds. One participant listened to piano notes (played live by a pianist) and to a home-office soundscape. Timing tests showed that the temporal precision of the system is very good. We calculated ERPs to sound onsets and observed the typical P1-N1-P2 complex of auditory processing. Furthermore, we show how to relate information on loudness (RMS) and spectra (PSD) to brain activity. In future studies, we can use this system to study sound processing in everyday life.


title: Learning about threat from friends and strangers is equally effective: an fMRI study on observational fear conditioning

abstract: Humans often benefit from social cues when learning about the world. For instance, learning about threats from others can save the individual from dangerous first-hand experiences. Familiarity is believed to increase the effectiveness of social learning, but it is not clear whether it plays a role in learning about threats. Using functional magnetic resonance imaging, we undertook a naturalistic approach and investigated whether there was a difference between observational fear learning from friends and strangers. Participants (observers) witnessed either their friends or strangers (demonstrators) receiving aversive (shock) stimuli paired with colored squares (observational learning stage). Subsequently, participants watched the same squares, but without receiving any shocks (direct-expression stage). We observed a similar pattern of brain activity in both groups of observers. Regions related to threat responses (amygdala, anterior insula, anterior cingulate cortex) and social perception (fusiform gyrus, posterior superior temporal sulcus) were activated during the observational phase, reflecting the fear contagion process. The anterior insula and anterior cingulate cortex were also activated during the subsequent stage, indicating the expression of learned threat. Because there were no differences between participants observing friends and strangers, we argue that social threat learning is independent of the level of familiarity with the demonstrator.


title: Molecular mechanisms associated with clustered lesion-induced impairment of 8-oxoG recognition by the human glycosylase OGG1

abstract: The 8-oxo-7,8-dihydroguanine, referred to as 8-oxoG, is a highly mutagenic DNA lesion that can provoke the appearance of mismatches if it escapes the DNA Damage Response. The specific recognition of its structural signature by the hOGG1 glycosylase is the first step along the Base Excision Repair pathway, that ensures the integrity of the genome by preventing the emergence of mutations. 8-oxoG formation, structural features and repair have been the matter of extensive research and more recently this active field of research expended to the more complicated case of 8-oxoG within clustered lesions. Indeed, the presence of a second lesion within 1 or 2 helix turns can dramatically impact the repair yields of 8-oxoG by glycosylases. In this work, we use s-range molecular dynamics simulations and machine learning-based post-analysis to explore the molecular mechanisms associated with the recognition of 8-oxoG by hOGG1 when embedded in a multiple lesions site with a mismatch in 5 or 3. We delineate the stiffening of the DNA-protein interactions upon the presence of the mismatches, and rationalize the much lower repair yields reported with a 5 mismatch by describing the perturbation of 8-oxoG structural features upon addition of an adjacent lesion.

category: biophysics


title: Glucosyltransferase-dependent and independent effects of Clostridioides difficile toxins during infection

abstract:
Clostridioides difficile infection (CDI) is the leading cause of nosocomial diarrhea and pseudomembranous colitis in the USA. In addition to these symptoms, patients with CDI can develop severe inflammation and tissue damage, resulting in life-threatening toxic megacolon. CDI is mediated by two large homologous protein toxins, TcdA and TcdB, that bind and hijack receptors to enter host cells where they use glucosyltransferase (GT) enzymes to inactivate Rho family GTPases. GT-dependent intoxication elicits cytopathic changes, cytokine production, and apoptosis. At higher concentrations TcdB induces GT-independent necrosis in cells and tissue by stimulating production of reactive oxygen species via recruitment of the NADPH oxidase complex. Although GT-independent necrosis has been observed in vitro, the relevance of this mechanism during CDI has remained an outstanding question in the field. In this study we generated novel C. difficile toxin mutants in the hypervirulent BI/NAP1/PCR-ribotype 027 R20291 strain to test the hypothesis that GT-independent epithelial damage occurs during CDI. Using the mouse model of CDI, we observed that epithelial damage occurs through a GT-independent process that is does not involve immune cell influx. The GT-activity of either toxin was sufficient to cause severe edema and inflammation, yet GT activity of both toxins was necessary to produce severe watery diarrhea. These results indicate that both TcdA and TcdB contribute to infection when present. Further, while inactivating GT activity of C. difficile toxins may suppress diarrhea and deleterious GT-dependent immune responses, the potential of severe GT-independent epithelial damage merits consideration when developing toxin-based therapeutics against CDI.

SIGNIFICANCEClostridioides difficile is the leading cause of antibiotic-associated diarrhea in hospitals worldwide. This bacterium produces two virulence factors, TcdA and TcdB, which are large protein toxins that enter host colon cells to cause inflammation, fluid secretion, and cell death. The enzymatic domain of TcdB is a target for novel C. difficile infection (CDI) therapeutics since it is considered the major factor in causing severe CDI. However, necrotic cell death due to non-enzymatic TcdB-host interactions have been reported in cell culture and intoxicated tissue. Here, we generated C. difficile strains with enzyme-inactive toxins to evaluate the role of each toxin in an animal model of CDI. We observe an additive role for TcdA and TcdB in disease and both glucosyltransferase-dependent and independent phenotypes. These findings are expected to inform the development of toxin-based CDI therapeutics.

category: pathology


title: A Comparison of Weighted Stochastic Simulation Methods

abstract: 1Rare events are of particular interest in biology because rare biochemical events may be catastrophic to a biological system. To estimate the probability of rare events, several weighted stochastic simulation methods have been developed. Unfortunately, the robustness of these methods is questionable. Here, an analysis of weighted stochastic simulation methods is presented. The methods considered here fail to accomplish the task of rare event simulation, in general, suggesting that new methods are necessary to adequately study rare biological events.


title: RIG-I uses its intrinsically disordered CARDs-Helicase linker in RNA proofreading functions

abstract: The innate immune receptor RIG-I provides the first line of defense against viral infections. Viral RNAs are recognized by the C-terminal domain (CTD) of RIG-I, but the RNA must engage the helicase domain to release the signaling domain CARDs from their autoinhibitory CARD2:Hel2i interactions. Because the helicase lacks RNA specificity, there must be mechanisms to proofread RNAs entering the helicase domain. Although such mechanisms are crucial in preventing aberrant immune responses by non-specific RNAs, they remain largely unknown. This study reveals a previously unknown proofreading mechanism that RIG-I uses to ensure the helicase engages RNAs chosen explicitly by the CTD. A crucial part of this mechanism involves the intrinsically disordered CARDs-Helicase Linker (CHL), which uses its negatively charged regions to electrostatically antagonize incoming RNAs. In addition to RNA gating, CHL is essential in stabilizing the CARD2:Hel2i interface. The CHL and CARD2:Hel2i interface work together, establishing a tunable gating mechanism that allows CTD-chosen RNAs to bind into the helicase while blocking non-specific RNAs. With its critical regulatory functions, CHL represents a novel target for RIG-I-based therapeutics.

category: biochemistry


title: Effects of the collagen-glycosaminoglycan mesh on gene expression as determined by using principal component analysis-based unsupervised feature extraction

abstract: Development of the medical applications for substances or materials that contact the cells is important. Hence, it is necessary to elucidate how substance that surround cells affect the gene expression during incubation. Here, we compared the gene expression profiles of cell lines that were in contact with the collagen-glycosaminoglycan mesh and control cells. Principal component analysis-based unsupervised feature extraction was applied to identify genes with altered expression during incubation in the treated cell lines but not in the controls. The identified genes were enriched in various biological terms. Our method also outperformed a conventional methodology, namely, gene selection based on linear regression with time course.


title: A novel view on the mechanism of biological activity of antifreeze proteins

abstract: The adaptation of organisms to sub-zero temperatures is an intriguing problem in biology and biotechnology. The ice-binding antifreeze proteins are known to be responsible for the adaptation, but the mechanism of their action is still far from being clear. Here we show that: (i) in contrast to common belief, ice-binding proteins do not reduce the water freezing temperature and even raise (1) the ice melting point; (ii) at sub-zero temperatures (to {approx} -30{degrees}C), ice can be formed only on ice-binding surfaces, but, for kinetic reasons, not in bulk water; (iii) living cells have some large surfaces, which can bind the antifreeze proteins. These facts allow suggesting that the task of antifreeze proteins is not to bind to the ice crystals already formed in the cell and stop their growth or rearrangement, but to bind to those cell surfaces where the ice nuclei can form, and thus to prevent ice formation completely.


title: Magnetic Particle Imaging is a sensitive in vivo imaging modality for the quantification of dendritic cell migration

abstract: Immunotherapies, such as dendritic cell- (DC-)based therapies, are useful for treating cancer as an alternative to or in combination with traditional therapies. Cells must migrate to lymphoid organs to be effective and the magnitude of the ensuing T cell response is proportional to the number of lymph node-migrated DC. With less than 10% of cells expected to reach their destination, there is a need for an imaging modality capable of sensitively and quantitatively detecting cells. MRI has been used to track DC using iron and 19F methods, with limitations. Quantification of iron-induced signal loss is indirect and challenging; 19F signal is directly quantifiable but lacks sensitivity. Magnetic Particle Imaging (MPI) directly detects superparamagnetic iron oxide nanoparticles (SPIO) and enables quantitation of low numbers of SPIO-labeled cells. Here we describe the first study using MPI to track and quantify the migration of DC, injected into the footpads of C57BL/6 mice, to the popliteal lymph nodes (pLNs). As DC migrate from the site of injection to the lymph nodes, we measured a decrease in signal in the footpads and an increase in signal at the pLNs. The presence of SPIO-labeled DC in nodes was validated by ex vivo MPI and histology. By measuring the iron mass per cell in samples of labeled cells, we were able to provide an estimate of cell number for each source of signal and we report a sensitivity of approximately 4000 cells in vivo and 2000 cells ex vivo. For some mice, MPI was compared to cellular MRI. We also bring attention to the issue of resolving unequal signals within close proximity, a challenge for many pre-clinical studies using a highly concentrated tracer bolus that over shadows nearby lower signals. This study demonstrates the clear advantage of MPI to detect and quantify cells in vivo, bridging the gap left by cellular MRI, and all other in vivo imaging modalities, and opening the door for quantitative imaging of cellular immunotherapies.


title: A science friction story. Molecular interactions in semiflexible polymer networks

abstract: Established model theories, developed to capture the mechanical behavior of soft complex materials composed of semiflexible polymers assume entropic interactions between filaments to determine the mechanical response. In recent studies, the general accepted tube model has been challenged in terms of its basic assumption about filament-filament interactions, but also because of its predictions regarding the frequency dependence of the elastic modulus in the intermediate frequency regime. A central question is how molecular interactions and friction between network constituents influence the rheological response of isotropic entangled networks of semiflexible polymers. It was shown that friction forces between aligned pairs of actin filaments are not negligible. Here, we systematically investigate the influence of friction forces and attractive interactions on network rheology by means of a targeted surface modification. We show that these forces have a qualitative and quantitative influence on the viscoelastic properties of semiflexible polymer networks and contribute to the response to nonlinear deformations. By comparing two polymer model systems with respect to their surface compositions we give a possible explanation about the origin of acting forces on a molecular level.


title: Computationally designed GPCR quaternary structures bias signaling pathway activation

abstract: Communication across membranes controls critical cellular processes and is achieved by receptors translating extracellular signals into selective cytoplasmic responses. While receptor tertiary structures can now be readily characterized, receptor associations into quaternary structures are very challenging to study and their implications in signal transduction remain poorly understood. Here, we report a computational approach for predicting membrane receptor self-associations, and designing receptor oligomers with various quaternary structures and signaling properties. Using this approach, we designed chemokine receptor CXCR4 dimers with reprogrammed stabilities, conformations, and abilities to activate distinct intracellular signaling proteins. In agreement with our predictions, the designed CXCR4s dimerized through distinct conformations and displayed different quaternary structural changes upon activation. Consistent with the active state models, all engineered CXCR4 oligomers activated the G protein Gi, but only a few specific dimer structures also recruited {beta}-arrestins. Overall, we demonstrate that quaternary structures represent an important unforeseen mechanism of receptor biased signaling and reveal the existence of a conformational switch at the dimer interface of several G protein-coupled receptors including CXCR4, mu-Opioid and type-2 Vasopressin receptors that selectively control the activation of G proteins vs {beta}-arrestin-mediated pathways. The approach should prove useful for predicting and designing receptor associations to uncover and reprogram selective cellular signaling functions.


title: Assessment of community efforts to advance computational prediction of protein-protein interactions

abstract: Comprehensive insights from the human protein-protein interaction (PPI) network, known as the human interactome, can provide important insights into the molecular mechanisms of complex biological processes and diseases. Despite the remarkable experimental efforts undertaken to date to determine the structure of the human interactome, many PPIs remain unmapped. Computational approaches, especially network-based methods, can facilitate the identification of new PPIs. Many such approaches have been proposed. However, a systematic evaluation of existing network-based methods in predicting PPIs is still lacking. Here, we report community efforts initiated by the International Network Medicine Consortium to benchmark the ability of 24 representative network-based methods to predict PPIs across five different interactomes, including a synthetic interactome generated by the duplication-mutation-complementation model, and the interactomes of four different organisms: A. thaliana, C. elegans, S. cerevisiae, and H. sapiens. We selected the top-seven methods through a computational validation on the human interactome. We next experimentally validated their top-500 predicted PPIs (in total 3,276 predicted PPIs) using the yeast two-hybrid assay, finding 1,177 new human PPIs (involving 633 proteins). Our results indicate that task-tailored similarity-based methods, which leverage the underlying network characteristics of PPIs, show superior performance over other general link prediction methods. Through experimental validation, we confirmed that the top-ranking methods show promising performance externally. For example, from the top 500 PPIs predicted by an advanced similarity-base method [MPS(B&T)], 430 were successfully tested by Y2H with 376 testing positive, yielding a precision of 87.4%. These results establish advanced similarity-based methods as powerful tools for the prediction of human PPIs.


title: Mechanosensitive control of mitotic entry

abstract:
As cells prepare to divide, they must ensure that enough space is available to assemble the mitotic machinery without perturbing tissue homeostasis1. To do so, cells undergo a series of biochemical reactions regulated by cyclin B1-CDK1 that trigger the reorganization of the actomyosin cytoskeleton2 and ensure the coordination of cytoplasmic and nuclear events3.

Along with the biochemical events that control mitotic entry, mechanical forces have recently emerged as important players in the regulation of cell cycle events4-6. However, the exact link between mechanical forces and the biochemical pathways that control mitotic progression remains to be established. Here, we identify a mechanical signal on the nucleus that helps set the time for nuclear envelope permeabilization (NEP) and mitotic entry. This signal relies on actomyosin contractility, which leads to nuclear unfolding during the G2-M transition, activating the stretch-sensitive cPLA2 on the nuclear envelope. This contributes to the spatiotemporal translocation of cyclin B1 to the nucleus. Our data demonstrate how nuclear mechanics during the G2-M transition contribute to timely and efficient mitotic spindle assembly and prevents chromosomal instability.

category: cell biology


title: Aldh2 dependent formaldehyde metabolism fuels purine demands in melanocyte stem cells

abstract:
Melanocyte stem cells (McSCs) in zebrafish serve as an on-demand source of melanocytes during growth and regeneration, but metabolic programs associated with their activation and regenerative processes are not well known. Here, using live imaging coupled with scRNA-sequencing, we discovered that quiescent McSCs during regeneration activate a dormant embryonic neural crest transcriptional program followed by an aldehyde dehydrogenase (Aldh) 2 metabolic switch to generate progeny. Unexpectedly, while ALDH2 is well known for its aldehyde clearing mechanisms we find that in regenerating McSCs, Aldh2 activity is required to generate formate - the one-carbon (1C) building block for nucleotide biosynthesis - through formaldehyde metabolism. Consequently, we find that disrupting the 1C cycle with low-doses of methotrexate caused melanocyte regeneration defects. In the absence of Aldh2, we find that purines (but not pyrimidines) are the metabolic end product sufficient for activated McSCs to generate progeny. Together, our work reveals McSCs undergo a two-step cell state transition during regeneration, and that the reaction products of Aldh2 enzymes have tissue-specific stem cell functions that meet metabolic demands in regeneration.

SUMMARY STATEMENTIn melanocyte regeneration, quiescent McSCs respond by re-expressing a neural crest identity, followed by an Aldh2-dependent metabolic switch to generate progeny.


title: Aldh2 is a lineage-specific metabolic gatekeeper in melanocyte stem cells


title: The connection between Rap1 and Talin1 in CD4+ T Lymphocytes

abstract: Agonist induced increase in integrin affinity for ligands (activation) plays a pivotal role in T cell trafficking and functions. Activation requires Rap1 GTPase-mediated recruitment of talin1 to the integrins in the plasma membrane. Rap1-interacting adaptor molecule (RIAM) is a Rap1 effector that serves this function in T cells. In addition, Rap1 directly binds to talin1 to enable integrin activation in platelets. Here, we assessed the relative contributions of the Rap1-talin1 interaction and RIAM and provide a complete accounting of the connections between Rap1 and talin1 that support integrin activation in conventional CD4+ (Tconv) and CD25HiFoxp3+CD4+ regulatory T (Treg) cells. Disruption of both Rap1 binding sites in talin1 (talin1 (R35E,R118E)) causes a partial defect in L{beta}2, 4{beta}1 and 4{beta}7 integrin activation in both Tconv and Treg cells with resulting defects in T cell homing and functions. Over-expression of RIAM bypasses the integrin activation defect in Tconv cells expressing talin1 (R35E,R118E), indicating that RIAM can substitute for Rap1 binding to talin in integrin activation. Conversely, deletion of RIAM in talin1 (R35E,R118E) Tconv cells abrogates activation of L{beta}2, 4{beta}1 and 4{beta}7. RIAM and lamellipodin (LPD) are mammalian members of the MRL protein family; LPD plays a more important role than RIAM in Treg cell integrin activation. Nevertheless, loss of RIAM profoundly exacerbates the defects in Treg cell function caused by the talin1 (R35E,R118E) mutation. Most importantly, deleting both MRL proteins combined with talin1 (R35E,R118E) phenocopies the complete lack of integrin activation observed in Rap1a/b null Treg cells. In sum, these data reveal the functionally significant connections between Rap1 and talin1 that enable L{beta}2, 4{beta}1 and 4{beta}7 integrin activation in T cells.


title: Hyperglycemia-induced alteration of ER redox homeostasis delays ER export of proinsulin

abstract: Defects in the pancreatic {beta}-cells secretion system are well-described in Type 2 diabetes (T2D) and include impaired proinsulin processing and a deficit in mature insulin-containing secretory granules; however, the cellular mechanisms underlying these defects and the contribution of hyperglycemia to this process remain poorly understood. Here, we used an in situ fluorescent pulse-chase strategy and proximity labeling-based quantitative proteomics analysis to study proinsulin trafficking and demonstrate a direct link to glucose metabolism via the production of redox intermediates that facilitate proinsulin export from the ER. We show that ER export of proinsulin is delayed in T2D models resulting in decreased insulin granule formation and further demonstrate this process can be regulated by NADPH and reducing equivalent availability. Together, these data highlight a critical role for nutrient metabolism and mitochondrial dysfunction in the maladaptive remodeling of the {beta}-cells secretory pathway in the decline of {beta}-cell function in T2D.


title: Nutrient metabolism regulates insulin granule formation in the pancreatic islet β-cell via ER redox homeostasis


title: Confined migration induces heterochromatin formation and alters chromatin accessibility

abstract: During migration, cells often squeeze through small constrictions, requiring extensive deformation. We hypothesized that the nuclear deformation associated with such confined migration could alter chromatin organization and function. Studying cells migrating through collagen matrices and microfluidic devices that mimic interstitial spaces in vivo, we found that confined migration results in increased H3K9me3 and H3K27me3 heterochromatin marks that persist for several days. This "confined migration-induced heterochromatin" (CMiH) was distinct from heterochromatin formation during migration initiation. CMiH predominantly decreased chromatin accessibility at intergenic regions near centromeres and telomeres, suggesting heterochromatin spreading from existing heterochromatin sites. Consistent with the overall decrease in chromatin accessibility, global transcription was decreased during confined migration. Intriguingly, we also identified increased accessibility at promoter regions of genes linked to chromatin silencing, tumor invasion, and DNA damage response. Inhibiting CMiH reduced migration speed, suggesting that CMiH promotes confined migration. Together, our findings indicate that confined migration induces chromatin changes that regulate cell migration and other cellular functions.


title: Transcriptome and miRNAome reveal components regulating primary thickening of bamboo shoots

abstract: Primary thickening determines bamboo yield and wood property. However, little is known about the regulatory networks involved in this process. The present study identified a total of 58,652 genes and 521 miRNAs via transcriptome and small RNA sequencing using the underground thickening shoot samples of wild type (WT) Moso bamboo (Phyllostachys edulis) and a thick wall (TW) variant (P. edulis cv. Pachyloen) at five developmental stages (WTS1/TWS1-WTS5/TWS5). A total of 11,636 (54.05%) differentially expressed genes (DEGs) and 515 (98.85%) differentially expressed miRNAs (DEmiRs) were identified from the WT, TW, and WTTW groups. The first two groups were composed of four pairwise combinations each between two successive stages (WTS2/TWS2_vs_WTS1/TWS1, WTS3/TWS3_vs_WTS2/TWS2, WTS4/TWS4_vs_WTS3/TWS3 and WTS5/TWS5_vs_WTS4/TWS4), and the WTTW group was composed of five between two relative stages (TWS1-5_vs_WTS1-5). Additionally, among the phytohormones, zeatin (ZT) showed more remarkable changes in concentrations than indole-3-acetic acid (IAA), gibberellic acid (GA3), and abscisic acid (ABA) throughout the five stages in the WT and the TW groups. Moreover, 118 sites were identified for 590 miRNA-mRNA pairs via degradome sequencing. The dual-luciferase reporter assay confirmed that 14 miRNAs bound to 12 targets. Fluorescence in situ hybridization (FISH) localized miR166 and miR160 in the shoot apical meristem (SAM) and the procambium of Moso bamboo shoots at the S1 stage. Thus, primary thickening is a complex process regulated by miRNA-gene-phytohormone networks, and the miRNAome and transcriptome dynamics regulate phenotypic plasticity. These findings provide insights into the molecular mechanisms underlying wood formation and properties and propose targets for bamboo breeding.

category: developmental biology


title: A Purkinje cell to parabrachial nucleus pathway enables broad cerebellar influence over the forebrain and emotional valence

abstract: In addition to its well-known contributions to motor control and motor learning, the cerebellum is involved in language, emotional regulation, anxiety, and affect1-4. We found that suppressing the firing of cerebellar Purkinje cells (PCs) rapidly excites forebrain areas that could contribute to such functions, including the amygdala, basal forebrain, and septum, but that the classic cerebellar outputs, the deep cerebellar nuclei (DCN), do not project to these regions. Here we show that parabrachial nuclei (PBN) neurons that receive direct PC input, project to and influence all of these forebrain regions and many others. Furthermore, the function of this pathway is distinct from the canonical pathway: suppressing PC to PBN activity is aversive, whereas suppressing the PC to DCN pathway is rewarding. Therefore, the PBN pathway allows the cerebellum to influence the entire spectrum of valence, modulate the activity of forebrain regions known to regulate diverse nonmotor behaviors, and may be the substrate for many nonmotor disorders related to cerebellar dysfunction.


title: A phylogenetically-restricted essential cell cycle progression factor in the human pathogen Candida albicans

abstract:
Chromosomal instability in fungal pathogens caused by cell division errors is associated with antifungal drug resistance. To identify mechanisms underlying such instability and to uncover new potential antifungal targets, we conducted an overexpression screen monitoring chromosomal stability in the human fungal pathogen Candida albicans. Analysis of ~1000 genes uncovered six chromosomal stability (CSA) genes, five of which are related to cell division genes in other organisms. The sixth gene, CSA6, is selectively present in the CUG-Ser clade species that includes C. albicans and other human fungal pathogens. The protein encoded by CSA6 localizes to the spindle pole bodies, is required for exit from mitosis, and induces a checkpoint-dependent metaphase arrest upon overexpression. Together, Csa6 defines an essential CUG-Ser fungal clade-specific cell cycle progression factor, highlighting the existence of phylogenetically-restricted cell division genes which may serve as potential unique therapeutic targets.

TeaserCsa6 is essential for mitotic progression and mitotic exit in the human fungal pathogen Candida albicans.


title: Top2a promotes the development of social behavior via PRC2 and H3K27me3

abstract: Human infants exhibit innate social behaviors at birth, yet little is understood about the embryonic development of sociality. We screened 1120 known drugs and found that embryonic inhibition of topoisomerase II (Top2a) resulted in lasting social deficits in zebrafish. In mice, prenatal Top2 inhibition caused behavioral defects related to core symptoms of autism, including impairments in social interaction and communication. Mutation of Top2a in zebrafish caused downregulation of a set of genes highly enriched for genes associated with autism in humans. Both the Top2a-regulated and autism-associated gene sets possess binding sites for polycomb repressive complex 2 (PRC2), a regulatory complex responsible for H3K27 trimethylation. Moreover, both gene sets are highly enriched for H3K27me3. Inhibition of PRC2 component Ezh2 rescued social deficits caused by Top2 inhibition. Therefore, Top2a is a key component of an evolutionarily conserved pathway that promotes the development of social behavior through PRC2 and H3K27me3.

category: animal behavior and cognition


title: Network rewiring promotes cooperation in an aspirational learning model

abstract:
We analyze a cooperative decision-making model that is based on individual aspiration levels using the framework of a public goods game in static and dynamic networks. Sensitivity to differences in payoff and dynamic aspiration levels modulate individual satisfaction and affects subsequent behavior. The collective outcome of such strategy changes depends on the efficiency with which aspiration levels are updated. Below a threshold learning efficiency, cooperators dominate despite short-term fluctuations in strategy fractions. Categorizing players based on their satisfaction level and the resulting strategy reveal periodic cycling between the different categories. We explain the distinct dynamics in the two phases in terms of differences in the dominant cyclic transitions between different categories of cooperators and defectors. Allowing even a small fraction of nodes to restructure their connections can promote cooperation across almost the entire range of values of learning efficiency. Our work reinforces the usefulness of an internal criterion for strategy updates, together with network restructuring, in ensuring the dominance of altruistic strategies over long time-scales.

Maintaining a public resource requires sustained cooperation through contributions by community members who benefit from it. Yet, a selfish individual who refuses to contribute can enjoy the benefits without paying the cost of sustaining the public good. If however, too many members of the community act selfishly, the public resource collapses to the detriment of all. The public goods game highlights such a social dilemma and provides a framework for exploring different mechanisms of strategic decision-making that allow cooperation and consequently the public good to be sustained. Among many mechanisms, the reorganization of social ties has been shown to be effective in promoting cooperation in PGG. However, the efficacy of most mechanisms in sustaining cooperation rely on individuals updating their strategy on the basis of information about the contributions of other members of the community. Often such information is either not forthcoming or cannot be effectively utilized. An alternative low-information model of behavioral updating relies on a comparison between the actual benefit received and the benefit aspired for. Individuals tend to retain their strategy if they are satisfied with the benefit received and change their strategy if they are unsatisfied. We show that such a simple reinforcement learning model along with modest restructuring of social ties over time can allow cooperation to be sustained. Our work shows that a low-information strategy-update model can be very effective in ensuring dominance of cooperators in social dilemmas.


title: Haemosporidian infection does not alter aerobic performance in the Pink-sided Junco (Junco hyemalis mearnsi)

abstract: Avian haemosporidia are blood parasites that can have dramatic fitness consequences on their hosts, including largescale population declines when introduced to naive hosts. Yet the physiological effects that accompany haemosporidian infection and underlie these fitness decrements are poorly characterized in most wild birds. Because haemosporidia destroy host red blood cells and consume host hemoglobin, they are predicted to have detrimental impacts on avian blood-oxygen transport and, as a result, reduce aerobic performance. However, the documented effects of infection on avian hematological traits vary across species and no effects have been demonstrated on avian aerobic performance to date. Here we quantified the physiological effects of haemosporidian infections on wild  Pink-sided Juncos (Junco hyemalis mearnsi) breeding in northwestern Wyoming, USA. We assayed hematological traits (hemoglobin concentration and hematocrit) and aerobic performance (resting and summit metabolic rates, thermogenic endurance, and aerobic scope), then screened individuals for haemosporidian infection post-hoc (n = 106 adult juncos). We found that infection status did not correlate with any of the physiological indices that we measured, suggesting there is little cost of haemosporidian infection on either junco aerobic performance or energy budgets. Our results highlight the need for more studies of haemosporidia infections in a broader range of species and in a wider array of environmental contexts.

category: physiology


title: The apportionment of citations: A scientometric analysis of Lewontin, 1972

abstract: "The Apportionment of Human Diversity" (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This studys primary result--that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences--along with Lewontins outspoken, politically-charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we show how the papers fame was shaped by four factors: 1) citations in influential publications across several disciplines; 2) Lewontins own popular books and media appearances; 3) the renaissance of population genetics research of the early 1990s; and 4) the serendipitous collision of scientific progress, influential books/papers, and heated controversies in the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the epicenter of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontins legacy.

category: scientific communication and education


title: Human primitive mesenchymal stem cell-derived retinal progenitor cells promoted neuroprotection and neurogenesis in rd12 mice

abstract: Retinal degenerative diseases (RDD) such as retinitis pigmentosa (RP) have no treatment. Stem cell-based therapies could provide promising opportunities to repair the damaged retina and restore vision. We investigated a novel approach in which human retinal progenitor cells (RPCs) derived from primitive mesenchymal stem cells (pMSCs) were examined to treat retinal degeneration in an rd12 mouse model of RP. Intravitreally transplanted cells improved retinal function and significantly increased retinal thickness. Transplanted cells homed, survived, and integrated to various retinal layers. They also induced anti-inflammatory and neuroprotective responses and upregulated neurogenesis genes. We found that RPCs were more efficacious than pMSCs in improving the retinal structure and function. RNA analyses suggest that RPCs promote neuroprotection and neuronal differentiation by activating JAK/STAT and MAPK, and inhibiting BMP signaling pathways. These promising results provide the basis for clinical studies to treat RDD using RPCs derived from pMSCs.


title: Lung epithelial CYP1 activity regulates aryl hydrocarbon receptor dependent allergic airway inflammation

abstract: The lung epithelial barrier serves as a guardian towards environmental insults and responds to allergen encounter with a cascade of immune reactions that can possibly lead to inflammation. Whether the environmental sensor aryl hydrocarbon receptor (AhR) together with its downstream targets cytochrome P450 (CYP1) family members contribute to the regulation of allergic airway inflammation remains unexplored. By employing knockout mice for AhR and for single CYP1 family members, we found that AhR-/- and CYP1B1-/- but not CYP1A1-/- or CYP1A2-/- animals display enhanced allergic airway inflammation compared to WT. Expression analysis, immunofluorescence staining of murine and human lung sections and bone marrow chimeras suggest an important role of CYP1B1 in non-hematopoietic lung epithelial cells to prevent exacerbation of allergic airway inflammation. Transcriptional analysis of murine and human lung epithelial cells indicates a functional link of AhR to barrier protection/inflammatory mediator signaling upon allergen challenge. In contrast, CYP1B1 deficiency leads to enhanced expression and activity of CYP1A1 in lung epithelial cells and to an increased availability of the AhR ligand kynurenic acid following allergen challenge. Thus, differential CYP1 family member expression and signaling via the AhR in epithelial cells represents an immunoregulatory layer protecting the lung from exacerbation of allergic airway inflammation.

category: immunology


title: Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets

abstract: Environmental scientists often have to predict a complex phenomenon from a heterogeneous collection of datasets. This is particularly challenging if there are systematic differences between them, as is often the case. Accounting for these differences requires a larger number of parameters and thus increases the risk of overfitting. We investigate how Bayesian hierarchical models can help mitigate this problem by allowing the practitioner to explicitly incorporate information about the dataset structure and general domain knowledge. To this end, we look at a typical application in remote sensing: the estimation of leaf area index (of white winter wheat), an important indicator for agronomical modeling, from measurements of reflectance spectra collected at different locations and growth stages. Since the insights gained from such a model could be used to inform policy or business decisions, the interpretability of the model is a primary concern. We, therefore, focus on models that capture the association between leaf area index and the spectral reflectance at various wavelengths by spline-based kernel functions, which can be visually inspected and analyzed. We compare models with three different levels of hierarchy: a non-hierarchical baseline model, a model with hierarchical bias parameter, and a model in which bias and kernel parameters are hierarchically structured. We analyze them using Markov Chain Monte Carlo sampling diagnostics and an intervention-based measure of feature importance. The improved robustness and interpretability of this approach lead us to recommend Bayesian hierarchical models as a versatile tool for environmental sciences and beyond, particularly in scenarios where the available data sources are heterogeneous.

category: ecology


title: Possible environmental and meteorological factors underlying scaly-breasted munia Lonchura punctulata (L.) mass mortality events in Southeast Asia urban and rural areas in September 2021

abstract: Mass bird mortality is a rare event. This event could be happened and could be a combination of numerous factors. It could be something thats still completely unknown to us. In September 2021 in SE Asia, there were 2 mass bird mortality events of Lonchura punctulata. The first event happens on 9 September in rural area at 08.00 AM and second happens on 14 September at 12.00 PM in urban area. The results show that precipitation combined with the wind gust might be correlated with mass mortality. The results showed precipitation factors have contributed 71.18% (R2 = 0.714, P = 0.008) to the mortality and followed by wind gust with 28.81% contribution (R2 = 0.41, P = 0.08). The meteorological parameter was not the only factors affecting the mortality events. The landscapes in urban and rural areas have experienced fragmentations. Urban areas have severe fragmentation of vegetation covers with remaining vegetation covers were only 17.4% and patch density indices of 0.29. In contrast rural areas still have higher vegetation cover remnants about 21.12% and patch density indices of 0.93. Then severe meteorological events combined with the fragmented habitats of L. punctulata may explain the mass mortality of this bird species.


title: Algebraic theorem of selection by spatial sorting

abstract: Heritable variation in traits that enhance dispersal rates can accumulate at population margins by spatial sorting. This mechanism of selection differs from natural selection as evolutionary change can ensue even in the absence of differential lifetime reproductive success. Although evidence suggests that populations are rapidly evolving at margins due to global change pressures, such as invasions and range shifts, we lack a mathematical theory of spatial sorting to understand these evolutionary patterns. To this end, we present an algebraic theorem, or the sorting theorem, to elucidate the nature of selection at margins, which can, in turn, facilitate axiomatic development of spatial sorting theory. The role of the sorting theorem in guiding research in this context is analogous to that of Prices theorem in natural selection theory.

category: evolutionary biology


title: Demographic Analysis of Mutations in Indian SARS-CoV-2 Isolates

abstract: In this study we carried out the early distribution of clades and subclades state-wise based on shared mutations in Indian SARS-CoV-2 isolates collected (27th Jan - 27th May 2020). Phylogenetic analysis of these isolates indicates multiple independent sources of introduction of the virus in the country, while principal component analysis revealed some state-specific clusters. It is observed that clade 20A defining mutations C241T (ORF1ab: 5 UTR), C3037T (ORF1ab: F924F), C14408T (ORF1ab: P4715L), and A23403G (S: D614G) are predominant in Indian isolates during this period. Higher number of coronavirus cases were observed in certain states, viz., Delhi, Tamil Nadu, and Telangana. Genetic analysis of isolates from these states revealed a cluster with shared mutations, C6312A (ORF1ab: T2016K), C13730T (ORF1ab: A4489V), C23929T, and C28311T (N: P13L). Analysis of region-specific shared mutations carried out to understand the large number of deaths in Gujarat and Maharashtra identified shared mutations defining subclade, I/GJ-20A (C18877T, C22444T, G25563T (ORF3a: H57Q), C26735T, C28854T (N: S194L), C2836T) in Gujarat and two sets of co-occurring mutations C313T, C5700A (ORF1ab: A1812D) and A29827T, G29830T in Maharashtra. From the genetic analysis of mutation spectra of Indian isolates, the insights gained in its transmission, geographic distribution, containment, and impact are discussed.


title: Identifying The "Core" Transcriptome of SARS-CoV-2 Infected Cells

abstract: In 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first emerged, causing the COVID-19 pandemic. Consequently, ongoing research has focused on better understanding the mechanisms underlying the symptoms of this disease. Although COVID-19 symptoms span a range of organ systems, the specific changes in gene regulation that lead to the variety of symptoms are still unclear. In our study, we used publicly available transcriptome data from previous studies on SARS-CoV-2 to identify commonly regulated genes across cardiomyocytes, human bronchial epithelial cells, alveolar type II cells, lung adenocarcinoma, human embryonic kidney cells, and patient samples. Additionally, using this common "core" transcriptome, we could identify the genes that were specifically and uniquely regulated in bronchial epithelial cells, embryonic kidney cells, or cardiomyocytes. For example, we found that genes related to cell metabolism were uniquely upregulated in kidney cells, providing us with the first mechanistic clue about specifically how kidney cells may be affected by SARS-CoV-2. Overall, our results uncover connections between the differential gene regulation in various cell types in response to the SARS-CoV-2 infection and help identify targets of potential therapeutics.


title: Image model embeddings for digital pathology and drug development via self-supervised learning

abstract:
Whole slide images (WSIs) contain rich pathology information which can be used to diagnose cancer, characterize the tumour microenvironment (TME), assess patient prognosis, and provide insights into the likelihood of whether a patient may respond to a given treatment. However, since WSI availability is generally scarce during early stage clinical trials, the applicability of deep learning models to new and ongoing drug development in early stages is typically limited. WSIs available in public repositories, such as The Cancer Genome Atlas (TCGA), enable an unsupervised pretraining approach to help alleviate data scarcity. Pretrained models can also be utilised for a range of downstream applications such as automated annotation, quality control (QC), and similar image search.

In this work we present DIME (Drug-development Image Model Embeddings), a pipeline for training image patch embeddings for WSIs via self-supervised learning. We compare inpainting and contrastive learning approaches for embedding training in the DIME pipeline, and demonstrate state-of-the-art performance at image patch clustering. In addition, we show that the resultant embeddings allow for training effective downstream patch classifiers with relatively few WSIs, and apply this to an AstraZeneca-sponsored phase III clinical trial. We also highlight the importance of effective colour normalisation for implementing histopathology analysis pipelines, regardless of the core learning algorithm. Finally, we show via subjective exploration of embedding spaces that the DIME pipeline clusters interesting histopathological artefacts, suggesting a possible role for the method in QC pipelines. By clustering image patches according to underlying morphopathologic features, DIME supports subsequent qualitative exploration by pathologists and has the potential to inform and expediate biomarker discovery and drug development.


title: CompoundRay: An open-source tool for high-speed and high-fidelity rendering of compound eyes

abstract: Revealing the functioning of non-standard visual systems such as compound eyes is of interest to biologists and engineers alike. A key investigative method is to replicate the sensory apparatus using artificial systems, allowing for investigation of the visual information that drives animal behaviour when exposed to environmental cues. To date,  Compound Eye Models (CEMs) have largely explored the impact of features such as spectral sensitivity, field of view, and angular resolution on behaviour. Yet, the role of shape and overall structure have been largely overlooked due to modelling complexity. However, modern real-time raytracing technologies are enabling the construction of a new generation of computationally fast, high-fidelity CEMs. This work introduces new open-source CEM software (CompoundRay) alongside standardised usage techniques, while also discussing the diffculties inherent with visual data display and analysis of compound eye perceptual data. CompoundRay is capable of accurately rendering the visual perspective of a desert ant at over 5,000 frames per second in a 3D mapped natural environment. It supports ommatidial arrangements at arbitrary positions with per-ommatidial heterogeneity.


title: Deciphering the role of the Pancreatic Secretome in Covid-19 associated Multi-Organ Dysfunctions

abstract: Emerging evidence indicates an intricate relationship between the SARS-CoV-2 infection and Multi-Organ Dysfunctions (MODs). Here, we have investigated the role of the Secretome of the SARS-CoV-2 infected pancreas and mechanistically linked it with the multi-organ dysfunction using the scRNA-seq analysis. We found that acinar-specific PRSS2, REG3A, REG1A, SPINK1, and ductal-specific SPP1, MMP7 genes are upregulated in alpha, beta, delta, and mesenchyme cells. Using extensive documented experimental evidence, we validated the association of upregulated pancreatic Secretome with coagulation cascade, complement activation, renin angiotensinogen system dysregulation, endothelial cell injury and thrombosis, immune system dysregulation, and fibrosis. Our finding suggests the influence of upregulated Secretome on multi-organ systems such as Nervous, Cardiovascular, Immune, Digestive, and Urogenital systems. In addition, we report that the secretory proteins IL1B, AGT, ALB, SPP1, CRP, SERPINA1, C3, TFRC, TNFSF10, and MIF are associated with diverse diseases. Thus, suggest the role of the pancreatic Secretome in SARS-CoV-2 associated MODs.


title: Balanced, Orientation-Dependent Dichoptic Masking in Cortex of Visually Normal Humans Measured Using Electroencephalography (EEG)

abstract: In the human visual system, cerebral cortex combines left- and right-eye retinal inputs, enabling single, comfortable binocular vision. In visual cortex, the signals from each eye inhibit one another (interocular suppression). While this mechanism may be disrupted by e.g. traumatic brain injury, clinical assessments of interocular suppression are subjective, qualitative, and lack reliability. EEG is a potentially useful clinical tool for objective, quantitative assessment of binocular vision. In a cohort of normal participants, we measured occipital, visual evoked potentials (VEPs) in response to dichoptically-presented vertical and/or horizontal sine-wave gratings. Response amplitudes to orthogonal gratings were greater than that of parallel gratings, which were in turn greater than that of monocular gratings. Our results indicate that interocular suppression is (normally) balanced, orientation-tuned, and that suppression per se is reduced for orthogonal gratings. This objective measure of suppression may have application in clinical settings.


title: Inducible CRISPR activation screen for interferon-stimulated genes identifies OAS1 as a SARS-CoV-2 restriction factor

abstract: Interferons establish an antiviral state in responding cells through the induction of hundreds of interferon-stimulated genes (ISGs). ISGs antagonize viral pathogens directly through diverse mechanisms acting at different stages of viral life cycles, and indirectly by modulating cell cycle and promoting programmed cell death. The mechanisms of action and viral specificities for most ISGs remain incompletely understood. To enable the high throughput interrogation of ISG antiviral functions in pooled genetic screens while mitigating the potentially confounding effects of endogenous IFN and potential antiproliferative/proapoptotic ISG activities, we adapted a CRISPR-activation (CRISPRa) system for inducible ISG induction in isogenic cell lines with and without the capacity to respond to IFN. Engineered CRISPRa cell lines demonstrated inducible, robust, and specific gRNA-directed expression of ISGs, which are functional in restricting viral infection. Using this platform, we screened for ISGs that restrict SARS-CoV-2, the causative agent of the COVID-19 pandemic. Results included ISGs previously described to restrict SARS-CoV-2 as well as multiple novel candidate antiviral factors. We validated a subset of candidate hits by complementary targeted CRISPRa and ectopic cDNA expression infection experiments, which, among other hits, confirmed OAS1 as a SARS-CoV-2 restriction factor. OAS1 exhibited strong antiviral effects against SARS-CoV-2, and these effects required OAS1 catalytic activity. These studies demonstrate a robust, high-throughput approach to assess antiviral functions within the ISG repertoire, exemplified by the identification of multiple novel SARS-CoV-2 restriction factors.

category: microbiology


title: Plant host shift: The viability and persistence of a polyphagous non-native insect

abstract: Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.


title: Plant host shift: The viability and persistence of a polyphagous, non-native insect


title: Plant-host shift, spatial persistence, and the viability of an invasive insect population


title: A Cellular Reference Resource for the Mouse Urinary Bladder

abstract: The urinary bladder functions as a reservoir to store and extrude liquid bodily waste. Significant debate exists as to this tissues cellular composition and genes associated with their functions. We use a repertoire of cell profiling tools to comprehensively define and spatial resolve cell types. We characterize spatially validated, basal-to-luminal gene expression dynamics within the urothelium, the cellular source of most bladder cancers. We define three distinct populations of fibroblasts that spatially organize from the sub-urothelial layer through to the detrusor muscle, clarifying knowledge around these controversial interstitial cells, and associate increased fibroblasts with aging. We overcome challenges of profiling the detrusor muscle, absence from earlier single cell studies, to report on its transcriptome with many novel and neuronal-like features presumably associated with neuromuscular junctions. Our approach provides a blueprint for tissue atlas construction and the data provides the foundation for future studies of bladder function in health and disease.

category: genomics


title: GBSmode: a pipeline for haplotype-aware analysis of genotyping-by-sequencing data

abstract:
2AO_SCPLOWBSTRACTC_SCPLOW2.1 BO_SCPLOWACKGROUNDC_SCPLOWGenotyping-by-sequencing (GBS) has revolutionised molecular genetic analysis. It enables simultaneous genotyping of thousands of DNA markers in the genome of any species. In contrast to whole-genome shotgun sequencing, GBS exploits a restriction enzyme to reduce genome complexity and directs the sequencing to begin at fixed digestion sites. However, currently used tools for the analysis of GBS data, such as SAMtools, often neglect the fundamental technical differences between GBS and shotgun sequencing.

2.2 RO_SCPLOWESULTSC_SCPLOWHere we present GBSmode, a dedicated pipeline to call DNA sequence variants using whole-read information from GBS data. It removes false positives by incorporating biological features such as the ploidy level and the number of possible alleles in the population under investigation. Comparison of GBSmode with SAMtools in an F2 population of rice (Oryza sativa L.) showed both identified a similar number of polymorphisms (13,449 and 14,445, respectively) with a high overlap (8,143). However, differences were found in the number of read misalignments (8.0% and 14.3% for GBSmode and SAMtools, respectively) and genotyping errors (5.0% and 8.3% for GBSmode and SAMtools, respectively). Further tests in a bi-parental F1 population of cassava (Manihot esculenta Crantz) showed GBSmode found 31,489 polymorphic loci, whereas the number was higher with SAMtools (43,860). However, this difference was mainly attributable to GBSmode rejecting 11,695 loci that were biologically not possible.

2.3 CO_SCPLOWONCLUSIONSC_SCPLOWThis study shows that GBSmode is a versatile tool for the analysis of GBS data. Moreover, GBSmode was able to reduce genotyping errors arising from read misalignments by combining haplotype data with biological information. Whilst other tools may find more markers, GBSmode is designed for accuracy.


title: ProteInfer: deep networks for protein functional inference

abstract:
Predicting the function of a protein from its amino acid sequence is a long-standing challenge in bioinformatics. Traditional approaches use sequence alignment to compare a query sequence either to thousands of models of protein families or to large databases of individual protein sequences. Here we instead employ deep convolutional neural networks to directly predict a variety of protein functions - EC numbers and GO terms - directly from an unaligned amino acid sequence. This approach provides precise predictions which complement alignment-based methods, and the computational efficiency of a single neural network permits novel and lightweight software interfaces, which we demonstrate with an in-browser graphical interface for protein function prediction in which all computation is performed on the users personal computer with no data uploaded to remote servers. Moreover, these models place full-length amino acid sequences into a generalised functional space, facilitating downstream analysis and interpretation. To read the interactive version of this paper, please visit https://google-research.github.io/proteinfer/

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461077v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@74f8f1org.highwire.dtl.DTLVardef@183ae0borg.highwire.dtl.DTLVardef@1754f3org.highwire.dtl.DTLVardef@1ca54f5_HPS_FORMAT_FIGEXP  M_FIG C_FIG QR code for the interactive version of this preprint at https://google-research.github.io/proteinfer/


title: Context-aware deconvolution of cell-cell communication with Tensor-cell2cell

abstract: Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities and Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.


title: Extracellular Vesicles Carry Distinct Proteo-Transcriptomic Signatures That are Different from Their Cancer Cell of Origin

abstract: Circulating extracellular vesicles (EVs) contain molecular footprints from their cell of origin and may provide potential non-invasive access for detection, characterization, and monitoring of numerous diseases. Despite their growing promise, the integrated proteo-transcriptomic landscape of EVs and their donor cells remain poorly understood. To assess their cargo, we conducted small RNA sequencing and mass spectrometry (LC-MS/MS) of EVs isolated from in vitro cancer cell culture and prostate cancer patients serum. Here, we report that EVs enrich for distinct molecular cargo, and their proteo-transcriptome is predominantly different from their cancer cell of origin, implicating a coordinated disposal and delivery mechanism. We have discovered that EVs package their cargo in a non-random fusion, as their most enriched RNAs and proteins are not the most abundant cargo from their donor cells. We show that EVs enrich for 4 times more cytoskeletal and 2 times extracellular proteins than their donor cells. While the donor cells carry 10 times more mitochondrial and 3 times nuclear proteins than their EVs. EVs predominantly (40-60%) enrich for small RNA (~15-200 nucleotides) molecules that implicate cell differentiation, development, and signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched of RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2), implicating an interrelated mechanism that may protect and regulate transcripts until a biological function is achieved. Based on these results, we envision that the next-generation clinical assays will take an integrative multi-omic (proteomic and transcriptomic) approach for liquid biopsy in numerous diseases.


title: Role of RALBP1 in Oxidative Stress and Mitochondrial Dysfunction in Alzheimer's Disease

abstract: The purpose of our study is to understand the role of the Ralbp1 gene in oxidative stress (OS), mitochondrial dysfunction and cognition in Alzheimers disease (AD) pathogenesis. The Ralbp1 gene encodes the 76 kDa protein Rlip (aka RLIP76). Previous studies have revealed its role in OS-related cancer. However, Rlip is transcriptionally regulated by EP300, a CREB-binding protein that is important for synaptic plasticity in the brain. Rlip functions as a stress-responsive/protective transporter of glutathione conjugates (GS-E) and xenobiotic toxins. OS causes rapid cellular accumulation of Rlip and its translocation from a tubulin-bound complex to the plasma membrane, mitochondria and nucleus. Therefore, Rlip may play an important role in maintaining cognitive function in the face of OS-related injury. This study is aimed to determine whether Rlip deficiency in mice is associated with AD-like cognitive and mitochondrial dysfunction. Brain tissue obtained from cohorts of wildtype and Rlip+/- mice were analyzed for OS markers, expression of genes that regulate mitochondrial fission/fusion, and synaptic integrity. We also examined mitochondrial ultrastructure in mouse brains obtained from these mice and further analyzed the impact of Rlip deficiency on gene networks of AD, aging, inhibition of stress-activated gene expression, mitochondrial function, and CREB signaling. Our studies revealed a significant increase in the levels of OS markers and alterations in the expression of genes and proteins involved in mitochondrial biogenesis, dynamics and synapses in brain tissues of these mice. Furthermore, we compared the cognitive function of wildtype and Rlip+/- mice. Behavioral, basic motor and sensory function tests in Rlip+/- mice revealed cognitive decline, similar to AD. Gene network analysis indicated dysregulation of stress-activated gene expression, mitochondrial function, and CREB signaling genes in the Rlip+/- mouse liver. Our results suggest that the Rlip deficiency-associated increase in OS and mitochondrial dysfunction could contribute to the development of OS-related AD processes. Therefore, the restoration of Rlip activity and endogenous cytoprotective mechanisms by pharmacological interventions is a novel approach to protect against AD.


title: Emotion Down- and Up-Regulation Act on Spatially Distinct Brain Areas:Interoceptive Regions to Calm Down and Other Affective Regions to Amp Up

abstract:
Prior studies on emotion regulation identified a set of brain regions specialized for generating and controlling affect. Researchers generally agree that when up- and down-regulating emotion, control regions in the prefrontal cortex turn up or down activity in affect-generating areas. However, the assumption that turning up and down emotions produces opposite effects in the same affect-generating regions is untested. We call this assumption the  affective dial hypothesis. Our study tested this hypothesis by examining the overlap between the sets of regions activated during up-regulation and those deactivated during down-regulation in a large number of participants (N=105). We found that up- and down-regulation both recruit regulatory regions such as the inferior frontal gyrus and dorsal anterior cingulate gyrus but act on distinct affect-generating regions. While up-regulation increases BOLD signal in regions associated with emotion such as the amygdala, anterior insula, striatum and anterior cingulate gyrus as well as in regions associated with sympathetic vascular activity such as periventricular white matter, down-regulation decreases signal in regions receiving interoceptive input such as the posterior insula and postcentral gyrus. These findings indicate that up- and down-regulation do not generally exert opposing effects on the same affect-generating regions. Instead, they target different brain circuits.

Significance StatementMany contexts require modulating ones own emotions. Identifying the brain areas implementing these regulatory processes should advance understanding emotional disorders and designing potential interventions. The emotion regulation field has an implicit assumption we call the affective dial hypothesis: that both emotion up- and down-regulation modulate the same emotion-generating brain areas. Countering the hypothesis, our findings indicate that up- and down-modulating emotions target different brain areas. Thus, the mechanisms underlying emotion regulation differ more than previously appreciated for up- versus down-regulation. In addition to their theoretical importance, these findings are critical for researchers attempting to target activity in particular brain regions during an emotion regulation intervention.


title: Early-life respiratory viral infection results in impairment of adult lung function

abstract: Respiratory viral infections in early-life are linked to the development of chronic lung diseases that persist into adulthood. The aim of this study was to develop a mouse model of early-life respiratory viral infection that would lead to impaired lung function in adulthood. BALB/c pups were infected at seven days of life with one of the following respiratory viruses: influenza A/Mem/1/71 "M71", influenza A/Puerto Rico/8/34 "PR8" or attenuated mengovirus "Mengo". Lung function and airways responsiveness (AHR) to methacholine were assessed seven weeks later, using the forced oscillation technique, and data were compared between male and female mice. PR8 infection was associated with significantly increased responsiveness to methacholine (for airway resistance, tissue damping, tissue elastance and hystersivity) for both sexes. M71 infection resulted in less severe responses especially in adult males. Early-life Mengo infection led to significantly higher responsiveness to MCh for males only (for airway resistance and tissue damping), suggesting sex dependant effects in lung function parameters measured. In summary, we have established a murine model where respiratory viral infection on day seven of life leads to AHR in adulthood. Importantly, the model recapitulates key variations in susceptibility related to sex and nature of viral pathogen that have previously been observed in human epidemiological studies. Our findings reveal new insights into the early origins of AHR and provide a tractable model system for future studies to unlock the mechanisms that determine pathogenesis.


title: Multiple stressors and recruitment failure of long-lived endangered freshwater mussels with a complex life cycle

abstract:
O_LIMultiple stressors can interactively affect the population of organisms; however, the process by which they affect recruitment efficiency remains unclear for empirical populations. Recruitment efficiency can be regulated at multiple stages of life, particularly in organisms with complex life cycles. Understanding the interactive effects of multiple stressors on recruitment efficiency and determining the bottleneck life stages is imperative for species conservation.
C_LIO_LIThe proportion of <20-year-old juveniles of the endangered freshwater pearl mussel Margaritifera togakushiensis, which has an obligate parasitic larval stage, was investigated in 24 rivers from eastern Hokkaido, northern Japan to reveal the influence of nutrients, fine sediment, and their combined effects on juvenile recruitment efficiency. The following indices for recruitment at adult, parasitic, and post-parasitic juvenile stages were obtained from 11 of these rivers: gravid female density, glochidia density (the number of glochidia infections per stream area), and juvenile survival rate. This study explored the bottleneck stages of recruitment efficiency and the interactive effects of the two stressors on these stages.
C_LIO_LITwenty-four population status assessments determined that the proportion of juveniles ranged from 0.00 to 0.53, and juveniles were absent from four rivers. The results showed that the parasitic and post-parasitic juvenile stages were bottlenecks for recruitment efficiency. Juvenile survival rates had a more significant positive effect on recruitment efficiency in rivers with a high glochidia density. Juvenile survival rate was decreased by the synergistic interaction of nutrients and fine sediment, although factors limiting glochidia density were not found.
C_LIO_LIThe nutrient concentration of rivers in the study region was well explained by the proportion of agricultural land cover and urban areas in the watersheds, but no relationship was detected between fine sediment abundance and land use.
C_LIO_LIThis study suggests that nutrient management at a catchment scale can be effective for re-establishing the recruitment of M. togakushiensis, particularly in rivers with a high content of fine sediments. The results also emphasise the importance of considering both parasitic and post-parasitic juvenile stages of mussels to maximise the positive effects of stressor mitigation.
C_LI


title: Seeing the Forest for the trees: Assessing genetic offset predictions with Gradient Forest

abstract: Gradient Forest (GF) is increasingly being used to forecast climate change impacts, but remains mostly untested for this purpose. We explore its robustness to assumption violations, and relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. Although we found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. It could also be confounded by neutral demography, genomic architecture, and the nature of the adaptive environment. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of forecasting maladaptation.


title: Proteomic analysis of coarse and fine skin tissues of Liaoning cashmere goat

abstract: Proteomics is the study of all proteins expressed by a cell or even an organism. However, knowledge of proteins that regulate the fineness of cashmere is limited. Liaoning Cashmere goat (LCG) is a valuable genetic resource of China. The skin samples of Liaoning cashmere goats during the growing period were collected performed Tandem Mass Tag (TMT) method and identified 117 differentially expressed proteins in CT_LCG (course type) and FT_LCG (fine type). To verify protein genes differentially expressed in LCG, we performed PRM validation on three candidate proteins (ALB, SDC1 and ITGB4) in CT-LCG and FT-LCG. Furthermore, primary metabolic process and lysosome are most enriched in the GO and KEGG pathways, respectively. In addition, we also derived a protein-protein interaction (PPI) regulatory network from the perspective of bioinformatics. This study sought to elucidate the molecular mechanism of differential proteins regulating cashmere fineness of Liaoning cashmere goats by using TMT quantitative proteomics analysis. Differentially expressed proteins ALB and SDC1 may regulate cashmere fineness, ITGB4 can be further studied as a promising protein. They can be used as key genes to lay a foundation for the study of cashmere fineness of Liaoning cashmere goats.

category: genetics


title: Controlling fibroblast fibrinolytic activity allows for the bio-engineering of stable connective tissue equivalents

abstract: In tissue engineering, cell origin is important to ensure outcome quality. However, the impact of the cell type chosen for seeding in a biocompatible matrix has been less investigated. Here, we investigated the capacity of primary and immortalized fibroblasts of distinct origins to degrade a gelatin/alginate/fibrin (GAF)-based biomaterial. We further established that fibrin was targeted by degradative fibroblasts through the secretion of fibrinolytic matrix-metalloproteinases (MMPs) and urokinase, two types of serine protease. Finally, we demonstrated that besides aprotinin, specific targeting of fibrinolytic MMPs and urokinase led to cell-laden GAF stability for at least several days. These results support the use of specific strategies to tune fibrin-based biomaterials degradation over time. It emphasizes the need to choose the right cell type and further bring targeted solutions to avoid the degradation of fibrin-containing hydrogels or bioinks.

category: bioengineering


title: Predicting brain atrophy from tau pathology: A summary of clinical findings and their translation into personalized models

abstract: For more than 25 years, the amyloid hypothesis-the paradigm that amyloid is the primary cause of Alzheimers disease-has dominated the Alzheimers community. Now, increasing evidence suggests that tissue atrophy and cognitive decline in Alzheimers disease are more closely linked to the amount and location of misfolded tau protein than to amyloid plaques. However, the precise correlation between tau pathology and tissue atrophy remains unknown. Here we integrate multiphysics modeling and Bayesian inference to create personalized tau-atrophy models using longitudinal clinical images from the the Alzheimers Disease Neuroimaging Initiative. For each subject, we infer three personalized parameters, the tau misfolding rate, the tau transport coefficient, and the tau-induced atrophy rate from four consecutive annual tau positron emission tomography scans and structural magnetic resonance images. Strikingly, the tau-induced atrophy coefficient of 0.13/year (95% CI: 0.097-0.189) was fairly consistent across all subjects suggesting a strong correlation between tau pathology and tissue atrophy. Our personalized whole brain atrophy rates of 0.68-1.68%/year (95% CI: 0.5-2.0) are elevated compared to healthy subjects and agree well with the atrophy rates of 1-3%/year reported for Alzheimers patients in the literature. Once comprehensively calibrated with a larger set of longitudinal images, our model has the potential to serve as a diagnostic and predictive tool to estimate future atrophy progression from clinical tau images on a personalized basis.


title: Minimum complexity drives regulatory logic in Boolean models of living systems

abstract: The properties of random Boolean networks as models of gene regulation have been investigated extensively by the statistical physics community. In the past two decades, there has been a dramatic increase in the reconstruction and analysis of Boolean models of biological networks. In such models, neither network topology nor Boolean functions (or logical update rules) should be expected to be random. In this contribution, we focus on biologically meaningful types of Boolean functions, and perform a systematic study of their preponderance in gene regulatory networks. By applying the k[P] classification based on number of inputs k and bias P of functions, we find that most Boolean functions astonishingly have odd bias in a reference biological dataset of 2687 functions compiled from published models. Subsequently, we are able to explain this observation along with the enrichment of read-once functions (RoFs) and its subset, nested canalyzing functions (NCFs), in the reference dataset in terms of two complexity measures: Boolean complexity based on string lengths in formal logic which is yet unexplored in the biological context, and the average sensitivity. Minimizing the Boolean complexity naturally sifts out a subset of odd-biased Boolean functions which happen to be the RoFs. Finally, we provide an analytical proof that NCFs minimize not only the Boolean complexity, but also the average sensitivity in their k[P] set.

category: systems biology