Neutralization of SARS-CoV-2 Omicron BA.2 by Therapeutic Monoclonal Antibodies Monoclonal antibody therapy for the treatment of SARS-CoV-2 infection has been highly successful in decreasing disease severity; however, the recent emergence of the heavily mutated Omicron variant has posed a challenge to this treatment strategy. The Omicron variant BA.1 has been found to evade neutralization by several of the therapeutic monoclonal antibodies authorized for emergency use, while Vir-7831 and a cocktail consisting of monoclonal antibodies AZD8895+AZD1061 retain significant neutralizing activity. A newly emerged variant, Omicron BA.2, containing some of the BA.1 mutations plus an additional 6 mutations and 3 deletions, 3 of which lie in the receptor binding domain, has been found to be spreading with increased transmissibility. We report here, using spike protein-pseudotyped lentiviruses, decreased neutralization of BA.2 by several therapeutic monoclonal antibodies but that the mixture of AZD8895+AZD1061 retained substantial neutralizing activity against BA.2.
Creation of a single cell RNA seq meta-atlas to define human liver immune homeostasis The liver is unique in both its ability to maintain immune homeostasis and in its potential for immune tolerance following solid organ transplantation. Single-cell RNA sequencing (scRNA seq) is a powerful approach to generate highly dimensional transcriptome data to understand cellular phenotypes. However, when scRNA data is produced by different groups, with different data models, different standards, and samples processed in different ways, it can be challenging to draw meaningful conclusions from the aggregated data. The goal of this study was to establish a method to combine  human liver scRNA seq datasets by 1) characterizing the heterogeneity between studies and 2) using the meta-atlas to define the dominant phenotypes across immune cell subpopulations in healthy human liver. Publicly available scRNA seq data generated from liver samples obtained from a combined total of 17 patients and [~]32,000 cells were analyzed. Liver-specific immune cells (CD45+) were extracted from each dataset, and immune cell subpopulations (myeloid cells, NK and T cells, plasma cells, and B cells) were examined using dimensionality reduction (UMAP), differential gene expression, and ingenuity pathway analysis. All datasets co-clustered, but cell proportions differed between studies. Gene expression correlation demonstrated similarity across all studies, and canonical pathways that differed between datasets were related to cell stress and oxidative phosphorylation rather than immune-related function. Next, a meta-atlas was generated via data integration and compared against PBMC data to define gene signatures for each hepatic immune subpopulation. This analysis defined key features of hepatic immune homeostasis, with decreased expression across immunologic pathways and enhancement of pathways involved with cell death. This method for meta-analysis of scRNA seq data provides a novel approach to broadly define the features of human liver immune homeostasis. Specific pathways and cellular phenotypes described in this human liver immune meta-atlas provide a critical reference point for further study of immune mediated disease processes within the liver.
The interplay of chromatin phase separation and lamina interactions in nuclear organization The genetic material of eukaryotes is segregated into transcriptionally active euchromatin and silent heterochromatin compartments. The spatial arrangement of chromatin compartments evolves over the course of cellular life in a process that remains poorly understood. The latest nuclear imaging experiments reveal a number of dynamical signatures of chromatin which are reminiscent of active multi-phase liquids. This includes the observations of viscoelastic response, coherent motions, Ostwald ripening and coalescence of chromatin compartments. There is also growing evidence that liquid-liquid phase separation of protein and nucleic acid components is the underlying mechanism for the dynamical behavior of chromatin. In order to dissect the organizational and dynamical implications of chromatins liquid behavior, we have devised a phenomenological field-theoretic model of nucleus as a multi-phase condensate of liquid chromatin types. Employing the liquid chromatin model of Drosophila nucleus, we have carried out an extensive set of simulations with an objective to shed light on the dynamics and chromatin patterning observed in the latest nuclear imaging experiments. Our simulations reveal the emergence of experimentally detected mesoscale chromatin channels and spheroidal droplets which arise from the dynamic interplay of chromatin type to type interactions and intermingling of chromosomal territories. We also quantitatively reproduce coherent motions of chromatin domains observed in displacement correlation spectroscopy measurements which are explained within the framework of our model by phase separation of chromatin types operating within constrained intra-chromosomal and inter-chromosomal boundaries. Finally, we illuminate the role of heterochromatin-lamina interactions in the nuclear organization by showing that these interactions enhance the mobility of euchromatin and indirectly introduce correlated motions of heterochromatin droplets.

SIGNIFICANCE STATEMENTThe latest super-resolution imaging experiments have revealed a surprisingly dynamic and stochastic nature of chromatin in eukaryotic nuclei which is reminiscent of multi-phase fluid behavior. As a result, the concepts from the theory of complex fluids such as phase separation, viscoelasticity, and droplet nucleation have found widespread utility in understanding salient features of nuclear organization. In order to understand and disentangle the complex interplay of forces that contribute to the emergent patterns of organization and dynamics, we have devised a phenomenological field-theoretic model of nucleus as a multi-phase condensate of liquid chromatin types. Armed with a mesoscopic model of nuclear chromatin, we have shed light on the distinct dynamical and structural contributions of chromatin type interactions intermingling of chromosomal territories and lamina binding. We also shed light on the dynamical heterogeneity and coherent motions of chromatin domains which are fully captured by an interplay of micro-phase separation of chromatin types and lamina binding. Active feature selection discovers minimal gene sets for classifying cell types and disease states with single-cell mRNA-seq data Sequencing costs currently prohibit the application of single-cell mRNA-seq to many biological and clinical analyses. Targeted single-cell mRNA-sequencing reduces sequencing costs by profiling reduced gene sets that capture biological information with a minimal number of genes. Here, we introduce an active learning method (ActiveSVM) that identifies minimal but highly-informative gene sets that enable the identification of cell-types, physiological states, and genetic perturbations in single-cell data using a small number of genes. Our active feature selection procedure generates minimal gene sets from single-cell data through an iterative cell-type classification task where misclassified cells are examined at each round of analysis to identify maximally informative genes through an  active support vector machine (ActiveSVM) classifier. By focusing computational resources on misclassified cells, ActiveSVM scales to analyze data sets with over a million single cells. We demonstrate that ActiveSVM feature selection identifies gene sets that enable 90% cell-type classification accuracy across a variety of data sets including cell atlas and disease characterization data sets. The method generalizes to reveal genes that respond to genetic perturbations and to identify region specific gene expression patterns in spatial transcriptomics data. The discovery of small but highly informative gene sets should enable substantial reductions in the number of measurements necessary for application of single-cell mRNA-seq to clinical tests, therapeutic discovery, and genetic screens. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. Stress fiber strain recognition by the LIM protein testin is cryptic and mediated by RhoA The actin cytoskeleton is a key regulator of mechanical processes in cells. The family of LIM domain proteins have recently emerged as important mechanoresponsive cytoskeletal elements capable of sensing strain in the actin cytoskeleton. The mechanisms regulating this mechanosensitive behavior, however, remain poorly understood. Here we show that the LIM domain protein testin is peculiar in that despite the full-length protein primarily appearing diffuse in the cytoplasm, the C-terminal LIM domains alone recognize focal adhesions and strained actin while the N-terminal domains alone recognize stress fibers. Phosphorylation mutations in the dimerization regions of testin, however, reveal its mechanosensitivity and cause it to relocate to focal adhesions and sites of strain in the actin cytoskeleton. Finally, we demonstrate activated RhoA causes testin to adorn stress fibers and become mechanosensitive. Together, our data show that testins mechanoresponse is regulated in cells and provide new insights into LIM domain protein recognition of the actin cytoskeleton mechanical state. Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. Ineffectual AEC1 differentiation from KRT8hi transitional state without fibrosis is associated with fatal COVID-19 ARDS ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Dramatic differences in male and female mortality trends for selected European cohorts over ~20 years. Longevity is of considerable interest. Collation of recent data after World War II by the Human Mortality Database allowed analyses, previously unattainable, of modal death-ages for sufficient numbers of selected European cohorts. The aim was to track modes and medians/means ([&ge;]60 years old (y)) of all-cause mortality for both sexes. The only highest-quality, large-number Lexis data available were analyzed: from nine countries: Denmark, Finland, France, Iceland, Italy, Netherlands, Norway, Sweden and Switzerland; raw-data modes (and medians/means [&ge;]60y, plus thin-plate-spline averages), were analyzed, plus pooled data. Here we show that for cohorts 1880-[~]1900 dramatic sex differences existed between death-age changes with all countries except Iceland showing male modal negative trends lasting [~]10-20 years and medians in all countries near-constant or negative lasting [~]10-20 years; whereas females from most countries showed fairly constant positive trends (except Finnish modes and Norwegian medians). For cohorts [~]1900-1919 male and female modal trends were positive (except Dutch and Icelandic cohorts and Finnish females). The net results were that male mortality modes for Danish, Icelandic, Italian, Dutch, Swedish and Norwegian 1919 cohorts were roughly the same as for 1880 cohorts, whereas female death-age modes increased. Results clarify previously knowledge concerning sex differences during this period. Despite improved environment in late adulthood over this period, this did not translate into increased male longevity and earlier events might have sealed their fate, especially in Denmark, Italy, Netherlands, Norway, aand Sweden (and, later, Iceland). F1F0 ATP Hydrolysis is a Determinant of Metabolic Rate, a Correlate of Lifespan, and a Weakness of Cancer Dramatic rectal temperature decrease, in mice administered with a drug that specifically inhibits F1F0 ATP hydrolysis, suggests that F1F0 ATP hydrolysis is a major determinant of metabolic rate in vivo. Across twelve investigated species, less F1F0 ATP hydrolysis correlates with greater maximal lifespan. Specific drug inhibition of F1F0 ATP hydrolysis exerts potent anti-cancer activity in vitro. Dynamic and stationary brain connectivity during movie watching as revealed by functional MRI Spatially remote brain regions show synchronized activity as typically revealed by correlated functional MRI (fMRI) signals. An emerging line of research has focused on the temporal fluctuations of connectivity; however, its relationships with stationary connectivity have not been clearly illustrated. We examined dynamic and stationary connectivity when the participants watched four different movie clips. We calculated point-by-point multiplication between two regional time series to estimate the time-resolved dynamic connectivity, and estimated the inter-individual consistency of the dynamic connectivity time series. Widespread consistent dynamic connectivity was observed for each movie clip, which also showed differences between the clips. For example, a cartoon movie clip, Wall-E, showed more consistent of dynamic connectivity with the posterior cingulate cortex and supramarginal gyrus, while a court drama clip, A Few Good Men, showed more consistent of dynamic connectivity with the auditory cortex and temporoparietal junction, which might suggest the involvement of specific brain processing for different movie contents. In contrast, the stationary connectivity as measured by the correlations between regional time series was highly similar among the movie clips, and showed fewer statistically significant differences. The patterns of consistent dynamic connectivity could be used to classify different movie clips with higher accuracy than the stationary connectivity and regional activity. These results support the functional significance of dynamic connectivity in reflecting functional brain changes, which could provide more functionally relevant information than stationary connectivity. Effects of phenotypic variation on consumer coexistence and prey community structure A popular idea in ecology is that trait variation among individuals from the same species may promote the coexistence of competing species. However, theoretical and empirical tests of this idea have yielded inconsistent findings. We manipulated intraspecific trait diversity in a ciliate competing with a nematode for bacterial prey in experimental microcosms. We found that intraspecific trait variation inverted the original competitive hierarchy to favor the consumer with variable traits, ultimately resulting in competitive exclusion. This competitive outcome was driven by foraging traits (size, speed, and directionality) that increased the ciliates fitness ratio and niche overlap with the nematode. The interplay between consumer trait variation and competition resulted in non-additive cascading effects - mediated through prey defense traits - on prey community assembly. Our results suggest that predicting consumer competitive population dynamics and the assembly of prey communities will require understanding the complexities of trait variation within consumer species. An NLR Integrated Domain toolkit to identify plant pathogen effector targets Plant resistance genes (or NLR "Nod-like Receptors") are known to contain atypical domains procuring them with a decoy capacity. Some of these integrated domains (or ID) allow the plant to lure the virulence determinants ("effectors") of pathogens and triggering a specific NLR immune reaction.

In this work, our goal was to generate a library of known IDs that could be screened with plant pathogen effectors in order to identify putative new effector virulence targets and NLR-effector pairs.

We curated the IDs contained in NLRs from seven model and crop plant species. We cloned 52 IDs representing 31 distinct Pfam domains. This library was screened for interaction by yeast-two-hybrid with a set of 31 conserved Ralstonia solanacearum type III effectors. This screening and the further in planta interaction assay allowed us to identify three interactions, involving different IDs (kinase, DUF3542, WRKY) and two type III effectors (RipAE and PopP2).

PopP2 was found to physically interact with ID#85, an atypical WRKY domain integrated in the GmNLR-ID85 NLR protein from Soybean. Using a imaging method in living plant cells, we showed that PopP2 associates with ID#85 in the nucleus. But unlike the known WRKY-containing Arabidopsis RRS1-R NLR receptor, this newly identified soybean WRKY domain could not be acetylated by PopP2 and its atypical sequence (WRKYGKR) also probably renders it inefficient in plant immunity triggering.

This ID toolkit is available for screening with other plant pathogen effectors and should prove useful to discover new effectors targets and potentially engineer new plant resistance genes. Flexible reprogramming of Pristionchus pacificus motivation for attacking Caenorhabditis elegans in predator-prey competition Animals with diverse diets must adapt their food priorities to a wide variety of environmental conditions. This diet optimization problem is especially complex for predators that compete with prey for food. Although predator-prey competition is widespread and ecologically critical, it remains difficult to disentangle predatory and competitive motivations for attacking competing prey. Here, we dissect the foraging decisions of the omnivorous nematode Pristionchus pacificus to reveal that its seemingly failed predatory attempts against Caenorhabditis elegans are actually motivated acts of efficacious territorial aggression. While P. pacificus easily kills and eats larval C. elegans with a single bite, adult C. elegans typically survives and escapes from bites. However, nonfatal biting can provide competitive benefits by reducing access of adult C. elegans and its progeny to bacterial food that P. pacificus also eats. We show that P. pacificus considers costs and benefits of both predatory and territorial outcomes to decide which food goal, prey or bacteria, should guide its motivation for biting. These predatory and territorial motivations impose different sets of rules for adjusting willingness to bite in response to changes in bacterial abundance. In addition to biting, predatory and territorial motivations also influence which search tactic P. pacificus uses to increase encounters with C. elegans. When treated with an octopamine receptor antagonist, P. pacificus switches from territorial to predatory motivation for both biting and search. Overall, we demonstrate that P. pacificus assesses alternate outcomes of attacking C. elegans and flexibly reprograms its foraging strategy to prioritize either prey or bacterial food. Recovery of high-quality assembled genomes via metagenome binning guided with single-cell amplified genomes BackgroundObtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite the improved bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenomic binners often fail to obtain reliable MAGs, and thus, they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a single-cell genome-guided metagenome binning (MetaSAG) to reconstruct the strain-resolved genomes from microbial communities at once.

ResultsMetaSAG employs single-cell amplified genomes (SAGs) generated with microfluidic technology as binning guides to recover improved draft genomes with the metagenomic data. To assess the performance of reconstructing genomes from various microbial communities, we compared MetaSAG with four conventional metagenomic binners using a cell mock community, human gut microbiota, and skin microbiota samples. MetaSAG showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids compared to conventional binners in genome reconstruction from the cell mock community. In human microbiota samples, MetaSAG recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ and 65 showed >90% completeness) and 45 skin microbial genomes (10 HQ and 40 showed >90% completeness), respectively. Conventional binners recovered one Staphylococcus hominis genome, whereas MetaSAG recovered two S. hominis genomes from the identical skin microbiota sample. Single-cell sequencing indicated that these S. hominis genomes clearly derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had substantial lack or excess of the genome sequences and contamination of other Staphylococcus bacteria (S. epidermidis).

ConclusionsMetaSAG enabled us to obtain the strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. MetaSAG will provide HQ genomes that are difficult to obtain with metagenomic analyses alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks through microbial genomes. MetaSAG is available at https://github.com/kojiari/metasag. Structural and Functional Analyses Explain Pea KAI2 Receptor Diversity and Reveal Stereoselective Catalysis During Signal Perception KAI2 are plant /{beta} hydrolase receptors, which perceive smoke-derived butenolide signals (karrikins) and putative endogenous, yet unidentified phytohormones (KAI2-ligands, KLs). The number of functional KAI2 receptors varies among plant species. It has been suggested that KAI2 gene duplication and sub-functionalization plays an adaptative role for diverse environments or ligand diversification by altering the receptor responsiveness to specific KLs. Legumes represent one of the largest families of flowering plants and contain many essential agronomic crops. Prior to legume diversification, KAI2 underwent duplication, resulting in KAI2A and KAI2B. Integrating plant genetics, ligand perception and enzymatic assays, and protein crystallography, we demonstrate that Pisum sativum KAI2A and KAI2B act as receptors and enzymes with divergent ligand stereoselectivity. KAI2B has a stronger affinity than KAI2A towards the KAI2-ligand (-)-GR24 and remarkably hydrolyses a broader range of substrates including the strigolactone-like isomer (+)-GR24. We determine the crystal structures of PsKAI2B in apo and butenolide-bound states. The biochemical and structural analyses as well as recorded mass spectra of KAI2s reveal a transient intermediate on the catalytic serine and a stable adduct on the catalytic histidine, further illuminating the role of KAI2 not only as receptors but also as bona fide enzymes. Our work uncovers the stereoselectivity of ligand perception and catalysis by evolutionarily diverged KAI2 receptors in KAR/KL signaling pathways and proposes adaptive sensitivity to KAR/KL and strigolactone phytohormones by KAI2B. Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression level with cell volume While most genes expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiaes mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model. Phenotypic plasticity is aligned with phenological adaptation on both micro- and macroevolutionary timescales In seasonally-variable environments, phenotypic plasticity in phenology may be critical for adaptation to fluctuating environmental (temperature) conditions. Using an 18-generation longitudinal dataset from natural insect (damselfly) populations, we show that phenology has strongly advanced. Individual fitness data suggest this is likely an adaptive response towards a thermally-dependent fitness optimum. A laboratory experiment revealed that developmental plasticity qualitatively matches environmental-dependence of selection, partially explaining observed phenological advance. Expanding our analysis to the macroevolutionary level, we use a database of over 1-million occurrence records and spatiotemporally-matched temperature data from 49 Swedish Odonate species to infer macroevolutionary dynamics of phenology. Phenological plasticity was more closely aligned with adaptation for species that have recently colonized northern latitudes, with more phenological mismatch at lower latitudes. Our results show that phenological plasticity plays a key role in microevolutionary dynamics within a single species, and such plasticity may have facilitated post-Pleistocene range expansion in this insect clade. Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Predicting gene regulatory networks from multi-omics to link genetic risk variants and neuroimmunology to Alzheimers disease phenotypes BackgroundGenome-wide association studies have found many genetic risk variants associated with Alzheimers disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. To address these problems, we performed an integrative multi-omics analysis of genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.

MethodFirst, given the population gene expression data of a cohort, we construct and cluster its gene co-expression network to identify gene co-expression modules for various AD phenotypes. Next, we predict transcription factors (TFs) regulating co-expressed genes and AD risk SNPs that interrupt TF binding sites on regulatory elements. Finally, we construct a gene regulatory network (GRN) linking SNPs, interrupted TFs, and regulatory elements to target genes and gene modules for each phenotype in the cohort. This network thus provides systematic insights into gene regulatory mechanisms from risk variants to AD phenotypes.

ResultsOur analysis predicted GRNs in three major AD-relevant regions: Hippocampus, Dorsolateral Prefrontal Cortex (DLPFC), Lateral Temporal Lobe (LTL). Comparative analyses revealed cross-region-conserved and region-specific GRNs, in which many immunological genes are present. For instance, SNPs rs13404184 and rs61068452 disrupt SPI1 binding and regulation of AD gene INPP5D in the Hippocampus and LTL. However, SNP rs117863556 interrupts bindings of REST to regulate GAB2 in DLPFC only. Driven by emerging neuroinflammation in AD, we used Covid-19 as a proxy to identify possible regulatory mechanisms for neuroimmunology in AD. To this end, we looked at the GRN subnetworks relating to genes from shared AD-Covid pathways. From those subnetworks, our machine learning analysis prioritized the AD-Covid genes for predicting Covid-19 severity. Decision Curve Analysis also validated our AD-Covid genes outperform known Covid-19 genes for classifying severe Covid-19 patients. This suggests AD-Covid genes along with linked SNPs can be potential novel biomarkers for neuroimmunology in AD. Finally, our results are open-source available as a comprehensive functional genomic map for AD, providing a deeper mechanistic understanding of the interplay among multi-omics, brain regions, gene functions like neuroimmunology, and phenotypes. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Synthesizing VERDICT maps from standard DWI data using GANs VERDICT maps have shown promising results in clinical settings discriminating normal from malignant tissue and identifying specific Gleason grades non-invasively. However, the quantitative estimation of VERDICT maps requires a specific diffusion-weighed imaging (DWI) acquisition. In this study we investigate the feasibility of synthesizing VERDICT maps from standard DWI data from multi-parametric (mp)- MRI by employing conditional generative adversarial networks (GANs). We use data from 67 patients who underwent both standard DWI-MRI and VERDICT MRI and rely on correlation analysis and mean squared error to quantitatively evaluate the quality of the synthetic VERDICT maps. Quantitative results show that the mean values of tumour areas in the synthetic and the real VERDICT maps were strongly correlated while qualitative results indicate that our method can generate realistic VERDICT maps that could supplement mp-MRI assessment for better diagnosis. Overexpression-based detection of translatable circular RNAs is vulnerable to coexistent linear RNA byproducts In RNA field, the demarcation between coding and non-coding has been negotiated by the recent discovery of occasionally translated circular RNAs (circRNAs). Although absent of 5 cap structure, circRNAs can be translated cap-independently. Complementary intron-mediated overexpression is one of the most utilized methodologies for circRNA research but not without bearing echoing skepticism for its poorly defined mechanism and latent coexistent side products. In this study, leveraging such circRNA overexpression system, we have interrogated the protein-coding potential of 30 human circRNAs containing infinite open reading frames in HEK293T cells. Surprisingly, pervasive translation signals are detected by immunoblotting. However, intensive mutagenesis reveals that numerous translation signals are generated independently of circRNA synthesis. We have developed a dual tag strategy to isolate translation noise and directly demonstrate that the fallacious translation signals originate from cryptically spliced linear transcripts. The concomitant linear RNA byproducts, presumably concatemers, can be translated to allow pseudo rolling circle translation signals, and can involve backsplicing junction (BSJ) to disqualify the BSJ-based evidence for circRNA translation. We also find non-AUG start codons may engage in the translation initiation of circRNAs. Taken together, our systematic evaluation sheds light on heterogeneous translational outputs from circRNA overexpression vector and comes with a caveat that ectopic overexpression technique necessitates extremely rigorous control setup in circRNA translation and functional investigation. Polycomb suppresses a female gene regulatory network to ensure testicular differentiation Gonadal sex determination is controlled by the support cells of testes and ovaries. In testes, the epigenetic mechanism that maintains cellular memory to suppress female sexual differentiation remains unknown. Here, we show that Polycomb suppresses a female gene regulatory network in Sertoli cells, the specific support cells for postnatal testes. Through genetic ablation, we removed Polycomb repressive complex 1 (PRC1) from embryonic Sertoli cells after sex determination. PRC1-depleted postnatal Sertoli cells exhibited defective proliferation and cell death, leading to the degeneration of adult testes. In adult Sertoli cells, PRC1 suppressed the specific, critical genes required for granulosa cells, the support cells of ovaries, thereby inactivating the female gene regulatory network. The underlying chromatin of female genes was coated with Polycomb-mediated repressive modifications: PRC1-mediated H2AK119ub and PRC2-mediated H3K27me3. Taken together, we identify a critical mechanism centered on Polycomb that maintains the male fate in adult testes. Chemotherapy coupled to macrophage inhibition leads to enhanced T and B cell infiltration and durable triple negative breast cancer regression Immunosuppressive elements within the tumor microenvironment such as Tumor Associated Macrophages (TAMs) can present a barrier to successful anti-tumor responses by cytolytic T cells. We employed preclinical syngeneic p53 null mouse models of triple negative breast cancer (TNBC) to develop a treatment regimen that harnessed the immunostimulatory effects of low-dose cyclophosphamide coupled with the pharmacologic inhibition of TAMs using either a small molecule CSF1R inhibitor or an anti-CSF1R antibody. This therapeutic combination was used to successfully treat several highly aggressive TNBC murine mammary tumors and lung metastasis. Using this regimen and single cell RNA sequencing we characterized tumor infiltrating lymphocytes (TILs) including helper T cells and antigen-presenting B cells that were highly enriched in good responders to combination therapy. Using high dimensional imaging techniques, we identified the close spatial localization of B220+ CD86+ activated B cells and CD4+ T cells in tertiary lymphoid structures that were present up to 6 weeks post-treatment in one model that also exhibited long-term tumor regression post-treatment. We also characterized the transcriptional and metabolic heterogeneity of TAMS in these two closely related claudin-low/mesenchymal subtype tumor models with differential treatment responses. A murine TAM signature derived from the T12 model is highly expressed and conserved in human claudin-low breast cancers, and high expression of the T12 signature correlated with reduced overall survival. This T12 tumor TAM signature may help identify human claudin-low breast cancer patients that will benefit from the combination of cyclophosphamide and anti-CSF1R therapy. These studies illustrate the complexity of the tumor immune microenvironment and highlight different immune responses that result from rationale combinations of immunotherapy.

SignificanceA treatment regimen that harnessed the immunostimulatory effects of cyclophosphamide coupled with the inhibition of CSF1R was used to successfully treat several highly aggressive claudin-low TNBC murine mammary tumors and lung metastasis.