Novel feature selection method via kernel tensor decomposition for improved multi-omics data analysis BackgroundFeature selection of multi-omics data analysis remains challenging owing to the size of omics datasets, comprising approximately 102-105 features. In particular, appropriate methods to weight individual omics datasets are unclear, and the approach adopted has substantial consequences for feature selection. In this study, we extended a recently proposed kernel tensor decomposition (KTD)-based unsupervised feature extraction (FE) method to integrate multi-omics datasets obtained from common samples in a weight-free manner.

MethodKTD-based unsupervised FE was reformatted as the collection of kernelized tensors sharing common samples, which was applied to synthetic and real datasets.

ResultsThe proposed advanced KTD-based unsupervised FE method showed comparative performance to that of the previously proposed KTD method, as well as tensor decomposition-based unsupervised FE, but required reduced memory and central processing unit time. Moreover, this advanced KTD method, specifically designed for multi-omics analysis, attributes P-values to features, which is rare for existing multi-omics-oriented methods.

ConclusionsThe sample R code is available at https://github.com/tagtag/MultiR/
Inference of disease-associated microbial biomarkers based on metagenomic and metatranscriptomic data The identification of disease-associated microbial biomarkers is crucial for disease diagnosis and therapy. However, the heterogeneity, high dimensionality, and large amounts of microbial data present tremendous challenges for the discovery of biomarkers. In this paper, we present IDAM, a novel method for disease-associated biomarker inference from metagenomic and metatranscriptomic data, which does not require prior metadata. This method integrates gene context conservation (uber-operon) and regulatory mechanisms (gene co-expression patterns), using a mathematical graph model. We demonstrated the excellent performance of IDAM in biomarker inference, through the datasets from inflammatory bowel disease, melanoma, type 1 diabetes mellitus, and irritable bowel syndrome. The software of IDAM is freely available at https://github.com/OSU-BMBL/IDAM.
Competition and environmental gradients structure assemblages of Canidae across the planet The phylogenetic information of assemblages carries the signature of ecological and evolutionary processes that assembled these communities. Identifying the mechanisms that shape communities is not simple, as they can vary spatially. Here, we investigated how the phylogenetic structure of Canidae across the globe is affected by the environment and competition. We first identified phylogenetically clustered and overdispersed assemblages of canids over the planet taking into account regional pools of species in South and North America, Eurasia, and Africa. Then, we applied Structural Equation Models in these communities in order to identify the effect of temperature, vegetation cover, human impact, and body size dissimilarity on the spatial distribution of the phylogenetic information of canids. Only southern South America and the Middle East had strong phylogenetic clustered patterns, while the rest of the planet predominantly showed overdispersed assemblages. Body size dissimilarity and vegetation cover were the most important variables to explain the spatial patterns of phylogenetic structure in clustered and overdispersed communities, respectively. Canidae community composition across the world presents significant patterns of clustering and overdispersion, which vary following mainly the environmental gradient, suggesting habitat filtering as the main force acting on Canidae assemblages. De novo chromosome-length assembly of the mule deer (Odocoileus hemionus) genome The mule deer (Odocoileus hemionus) is an ungulate species that ranges from western Canada to central Mexico. Mule deer are an essential source of food for many predators, are relatively abundant, and commonly make broad migration movements. A clearer understanding of the mule deer genome can help facilitate knowledge of its population genetics, movements, and demographic history, aiding in conservation efforts. While mule deer are excellent candidates for population genomic studies because of their large population size, continuous distribution, and diversity of habitat, few genomic resources are currently available for this species. Here, we sequence and assemble the mule deer genome into a highly contiguous chromosome-length assembly for use in future research using long-read sequencing and Hi-C. We also provide a genome annotation and compare demographic histories of the mule deer and white-tail deer using PSMC. We expect this assembly to be a valuable resource in the continued study and conservation of mule deer. Isolation of quenched light-harvesting complex II trimers from Arabidopsis leaves with sustained photoprotection (qH) Plants and algae are faced with a conundrum: harvesting sufficient light to drive their metabolic needs while dissipating light in excess to prevent photodamage, a process known as non-photochemical quenching. A slowly relaxing form of energy dissipation, termed qH, is critical for plants survival under abiotic stress. Here, we tested whether we could isolate photosynthetic subcomplexes (from plants in which qH was induced) that would remain in an energy-dissipative state. Interestingly chlorophyll fluorescence lifetimes were decreased by qH in isolated major trimeric antenna complexes, providing a natively quenched complex with physiological relevance to natural conditions. Next, we monitored the changes in thylakoid pigment, protein or lipid content of antenna with active or inactive qH, and no evident differences were detected. Finally, we investigated whether specific antenna subunits of the major antenna were required for qH but found it insensitive to trimer composition. Because qH can occur in the absence of specific xanthophylls, and no changes in pigments were detected, we propose that the energy-dissipative state reported here may stem from chlorophyll-chlorophyll excitonic interaction. The obstacles and potential clues of prime editing applications in tomato, a dicot plant Precision genome editing is highly desired for crop improvement. The recently emerged CRISPR/Cas technology offers great potential applications in precision plant genome engineering. A prime editing (PE) approach combining a reverse transcriptase (RT) with a Cas9 nickase and a "priming" extended guide RNA has shown a high frequency for precise genome modification in mammalian cells and several plant species. Nevertheless, the applications of the PE approach in dicot plants are still limited and inefficient. We designed and tested prime editors for precision editing of a synthetic sequence in a transient assay and for desirable alleles of 10 loci in tomato by stable transformation. Our data obtained by targeted deep sequencing also revealed only low PE efficiencies in both the tobacco and tomato systems. Further assessment of the activities of the PE components uncovered potential reasons for the inefficiency of the PE complexes. Modifying the pegRNA sequences by shortening or introducing mismatches to the primer binding sequences (PBS) in order to reduce their melting temperatures (Tm) did not enhance the PE efficiency at the SlBMP21, SlALC and SlALS1 loci. Our data show challenges of PE approach in tomato, indicating a further improvement of the PE system for the successful applications such as use of improved expression systems. Our work provides an important clue for the successful application of the PE approach in crop improvement. LPS-TLR4 pathway exaggerates alcohol-induced acute-on-chronic liver failure via provoking NETs formation Backgrounds: Intrahepatic infiltration of neutrophils is a character of alcoholic acute-on-chronic liver failure (AACLF) and neutrophil extracellular traps (NETs) are an important strategy for neutrophils to fix and kill invading microorganisms. Intestinal bacteria and the gut-liver axis have been thought to play a key role in many liver diseases also including AACLF. However, whether NETs appear in AACLF and play a role in AACLF is still unsure. Methods: WT, NE KO, and TLR4 KO mice were used to build the AACLF model, and the intestinal bacteria were eliminated at the same time and LPS was given. Then the formation of NETs and AACLF related markers were detected. Results: The serum MPO-DNA and LPS concentration was increased in AACLF patients and a correlation was revealed between these two indexes. More intrahepatic NETs formed in AACLF mice by testing MPO-DNA, Cit H3, and NE. These markers decreased with gut detergent and restored markers with gut detergent plus LPS supplement. While NETs formation failed to change with gut microbiome or combine LPS supplement in TLR4 KO mice. As we tested AACLF related characters, liver injury, intrahepatic fat deposition, inflammation, and fibrosis alleviated with depletion of NE. These related marks were also attenuated with gut sterilization by antibiotics and recovered with combined treatment with antibiotics plus LPS. But the liver injury, intrahepatic fat, fibro deposition, and liver inflammation-related markers did show a significant difference in TLR4 KO mice when they received the same treatment. Conclusion: Intestinal-derived LPS promotes NETs formation in AACLF through the TLR4 pathway and further accelerates the AACLF process by NETs. The Hippocampus uses cryptographic principles rather than plasticity to enable animals to secretly cache and retrieve their food For animals, the ability to hide and retrieve valuable information, such as the location of food, can mean the difference between life and death. Here, we propose that to achieve this, their brain uses spatial cells similarly to how we utilize encryption for data security. Some animals are able to cache hundreds of thousands of food items annually by each individual and later retrieve most of what they themselves stashed. Rather than memorizing their cache locations as previously suggested, we propose that they use a single cryptographic-like mechanism during both caching and retrieval. The model we developed is based on hippocampal spatial cells, which respond to an animals positional attention, such as when the animal enters a specific region (place-cells) or gazes at a particular location (spatial-view-cells). We know that the region that activates each spatial cell remains consistent across subsequent visits to the same area but not between areas. This remapping, combined with the uniqueness of cognitive maps, produces a persistent crypto-hash function for both food caching and retrieval. We also show that the model stores temporal information that helps animals in food caching order preference as previously observed. This behavior, which we refer to as crypto-taxis, might also explain consistent differences in decision-making when animals are faced with a large number of alternatives such as in foraging. Transcriptional Control of Brain Tumour Stem Cell by a Carbohydrate Binding Protein Brain tumour stem cells (BTSCs) and intratumoural heterogeneity represent major challenges in glioblastoma therapy. Here, we report that the LGALS1 gene, encoding the carbohydrate binding protein, galectin1, is a key regulator of BTSCs and glioblastoma resistance to therapy. Genetic deletion of LGALS1 alters BTSC gene expression profiles and results in downregulation of gene sets associated with mesenchymal subtype of glioblastoma. Using a combination of pharmacological and genetic approaches, we establish that inhibition of LGALS1 signalling in BTSCs impairs self-renewal, suppresses tumourigenesis, prolongs lifespan, and improves glioblastoma response to ionizing radiation in preclinical animal models. Mechanistically, we show that LGALS1 is a direct transcriptional target of STAT3 with its expression robustly regulated by the ligand OSM. Importantly, we establish that galectin1 forms a complex with the transcription factor HOXA5 to reprogram BTSC transcriptional landscape. Our data unravel an oncogenic signalling pathway by which galectin1/HOXA5 complex maintains BTSCs and promotes glioblastoma. Epidural Electrical Stimulation of the Cervical Dorsal Roots Restores Voluntary Upper Limb Control In Paralyzed Monkeys Recovering arm control is a top priority for people with paralysis. Unfortunately, the complexity of the neural mechanisms underlying arm control practically limited the effectiveness of neurotechnology approaches. Here, we exploited the neural function of surviving spinal circuits to restore voluntary arm and hand control in three monkeys with spinal cord injury using spinal cord stimulation. Our neural interface leverages the functional organization of the dorsal roots to convey artificial excitation via electrical stimulation to relevant spinal segments at appropriate movement phases. Stimulation bursts targeting specific spinal segments produced sustained arm movements enabling monkeys with arm paralysis to perform an unconstrained reach-and-grasp task. Stimulation specifically improved strength, task performances and movement quality. Electrophysiology suggested that residual descending inputs were necessary to produce coordinated movements. The efficacy and reliability of our approach hold realistic promises of clinical translation. One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction Machine learning (ML) is a key technology to enable accurate prediction of antibody-antigen binding, a prerequisite for in silico vaccine and antibody design. Two orthogonal problems hinder the current application of ML to antibody-specificity prediction and the benchmarking thereof: (i) The lack of a unified formalized mapping of immunological antibody specificity prediction problems into ML notation and (ii) the unavailability of large-scale training datasets. Here, we developed the Absolut! software suite that allows the parameter-based unconstrained generation of synthetic lattice-based 3D-antibody-antigen binding structures with ground-truth access to conformational paratope, epitope, and affinity. We show that Absolut!-generated datasets recapitulate critical biological sequence and structural features that render antibody-antigen binding prediction challenging. To demonstrate the immediate, high-throughput, and large-scale applicability of Absolut!, we have created an online database of 1 billion antibody-antigen structures, the extension of which is only constrained by moderate computational resources. We translated immunological antibody specificity prediction problems into ML tasks and used our database to investigate paratope-epitope binding prediction accuracy as a function of structural information encoding, dataset size, and ML method, which is unfeasible with existing experimental data. Furthermore, we found that in silico investigated conditions, predicted to increase antibody specificity prediction accuracy, align with and extend conclusions drawn from experimental antibody-antigen structural data. In summary, the Absolut! framework enables the development and benchmarking of ML strategies for biotherapeutics discovery and design.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/451258v2_ufig1.gif" ALT="Figure 1">
View larger version (81K):
org.highwire.dtl.DTLVardef@14295d2org.highwire.dtl.DTLVardef@7a12bdorg.highwire.dtl.DTLVardef@647102org.highwire.dtl.DTLVardef@375112_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical abstractC_FLOATNO The software framework Absolut! enables (A,B) the generation of virtually arbitrarily large numbers of in silico 3D-antibody-antigen structures, (C,D) the formalization of antibody specificity as machine learning (ML) tasks as well as the exploration of ML strategies for paratope-epitope prediction.

C_FIG Highlights- Software framework Absolut! to generate an arbitrarily large number of in silico 3D-antibody-antigen structures
- Generation of one billion in silico antigen-antibody structures reflecting biological layers of complexity that make ML predictions challenging
- Immunological antibody specificity prediction problems formalized as machine learning tasks for which the in silico complexes are immediately usable as benchmark.
- Exploration of machine learning architectures for paratope-epitope interaction prediction accuracy as a function of neural network depth, dataset size, and sequence-structure encoding Sources of information waste in neuroimaging:mishandling structures, thinking dichotomously, and over-reducing data Neuroimaging relies on separate statistical inferences at tens of thousands of spatial locations. Such massively univariate analysis typically requires an adjustment for multiple testing in an attempt to maintain the family-wise error rate at a nominal level of 5%. First, we examine three sources of substantial information loss that are associated with the common practice under the massively univariate framework: (a) the hierarchical data structures (spatial units and trials) are not well maintained in the modeling process; (b) the adjustment for multiple testing leads to an artificial step of strict thresholding; (c) information is excessively reduced during both modeling and result reporting. These sources of information loss have far-reaching impacts on result interpretability as well as reproducibility in neuroimaging. Second, to improve inference efficiency, predictive accuracy, and generalizability, we propose a Bayesian multilevel modeling framework that closely characterizes the data hierarchies across spatial units and experimental trials. Rather than analyzing the data in a way that first creates multiplicity and then resorts to a post hoc solution to address them, we suggest directly incorporating the cross-space information into one single model under the Bayesian framework (so there is no multiplicity issue). Third, regardless of the modeling framework one adopts, we make four actionable suggestions to alleviate information waste and to improve reproducibility: 1) abandon strict dichotomization, 2) report full results, 3) quantify effects, and 4) model data hierarchies. We provide examples for all of these points using both demo and real studies, including the recent NARPS investigation. Discovery of highly potent pancoronavirus fusion inhibitors that also effectively inhibit COVID-19 variants from the UK (Alpha), South Africa (Beta), and India (Delta) We report here the discovery of several highly potent small molecules that showed low nM potency against SARS-CoV (IC50: as low as 13 nM), SARS-CoV-2 (IC50: as low as 23 nM), and MERS-CoV (IC50: as low as 76 nM) in pseudovirus based assays with excellent selectivity indices (SI: as high as > 5000) demonstrating their pancoronavirus inhibition. Some compounds also show 100% inhibition of CPE (IC100) at 1.25 {micro}M against an authentic SARS-CoV-2 (US_WA-1/2020). Furthermore, the most active inhibitors also potently inhibited variants of concerns (VOCs), such as the UK (B.1.1.7), South Africa (B.1.351), and Delta variant (B.1.617.2), originated in India. We confirmed that one of the potent inhibitors binds to the prefusion spike protein trimer of SARS-CoV-2 by SPR. Besides, we showed that they inhibit virus-mediated cell-cell fusion. The ADME data of one of the most active inhibitors, NBCoV1, show drug-like properties. In vivo PK of NBCoV1 in rats demonstrated excellent half-life (t1/2) of 11.3 h, mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect the lead inhibitors to pave the way for further development to preclinical and clinical candidates. Global structural stability and the role of cooperation in mutualistic system Dynamical systems on graphs allow to describe multiple phenomena from different areas of Science. In particular, many complex systems in Ecology are studied by this approach. In this paper we analize the mathematical framework for the study of the structural stability of each stationary point, feasible or not, introducing a generalization for this concept, defined as Global Structural Stability. This approach would fit with the proper mathematical concept of structural stability, in which we find a full description of the complex dynamics on the phase space due to nonlinear dynamics. This fact can be analyzed as an informational field grounded in a global attractor whose structure can be completely characterized. These attractors are stable under perturbation and suppose the minimal structurally stable sets. We also study in detail, mathematically and computationally, the zones characterizing different levels of biodiversity in bipartite graphs describing mutualistic antagonistic systems of population dynamics. In particular, we investigate the dependence of the region of maximal biodiversity of a system on its connectivity matrix. On the other hand, as the network topology does not completely determine the robustness of the dynamics of a complex network, we study the correlation between structural stability and several graph measures. A systematic study on synthetic and biological graphs is presented, including 10 mutualistic networks of plants and seed-dispersal and 1000 random synthetic networks. We compare the role of centrality measures and modularity, concluding the importance of just cooperation strength among nodes when describing areas of maximal biodiversity. Indeed, we show that cooperation parameters are the central role for biodiversity while other measures act as secondary supporting functions.

Author summaryWe introduce the concept of Global Structural Stability as a proper mathematical concept to fully understand biodiversity in some ecological systems. Our concept retakes the definitions in the classical works of R. Thom [1] and Andronov-Pontryagin [2]. Moreover, there exists a close relation between the structure of a complex network, described as a graph, and its associated dynamics. Mutualistic networks introduce cooperation links between two groups of species, as plant and pollinators or seed-dispersal. The understanding of organizational aspects leading to maximizing biodiversity is one of the more important research areas in Theoretical and Applied Ecology. In this work we introduce a systematic study on different graph measures in order to identify optimal organization for maximal biodiversity (defined as structural stability). Our results conclude that, for mutualistic systems, the strength in cooperation parameters are the core fact, i.e., cooperation is the real fact optimizing biodiversity among other possible structural configurations. Highly efficient synthetic CRISPR RNA/Cas9-based mutagenesis for rapid cardiovascular phenotypic screening in F0 zebrafish The zebrafish is a valuable vertebrate model to study cardiovascular formation and function due to the facile visualization and rapid development of the circulatory system in its externally growing embryos. Despite having distinct advantages, zebrafish have paralogs of many important genes, making reverse genetics approaches inefficient since generating animals bearing multiple gene mutations requires substantial efforts. Here, we present a simple and robust synthetic CRISPR RNA/Cas9-based mutagenesis approach for generating biallelic F0 zebrafish knockouts. Using a dual-guide synthetic CRISPR RNA/Cas9 ribonucleoprotein (dgRNP) system, we compared the efficiency of biallelic gene disruptions following the injections of one, two, and three dgRNPs per gene into the cytoplasm or yolk. We show that simultaneous cytoplasmic injections of three distinct dgRNPs per gene into one-cell stage embryos resulted in the most efficient and consistent biallelic gene disruptions. Importantly, this triple dgRNP approach enables efficient inactivation of cell autonomous and cell non-autonomous gene function, likely due to the low mosaicism of biallelic disruptions. In support of this finding, we provide evidence that the F0 animals generated by this method fully phenocopied the endothelial and peri-vascular defects observed in corresponding stable mutant homozygotes. Moreover, this approach faithfully recapitulated the trunk vessel phenotypes resulting from the genetic interaction between two vegfr2 zebrafish paralogs. Mechanistically, investigation of genome editing and mRNA decay indicates that the combined mutagenic actions of three dgRNPs per gene lead to an increased probability of frameshift mutations, enabling efficient biallelic gene disruptions. Therefore, our approach offers a highly robust genetic platform to quickly assess novel and redundant gene function in F0 zebrafish. 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. Microtubule poleward flux promotes chromosome centering on the spindle Chromosome alignment at the spindle equator promotes proper chromosome segregation and depends on pulling forces exerted at kinetochore fiber tips together with polar ejection forces. However, kinetochore fibers are also subjected to forces driving their poleward flux. Here we introduce a flux-driven centering model that relies on flux generated by forces within the overlaps of bridging and kinetochore fibers. This centering mechanism works so that the longer kinetochore fiber fluxes faster than the shorter one, moving the kinetochores towards the center. We developed speckle microscopy in human spindles and confirmed the key prediction that kinetochore fiber flux is length-dependent. Kinetochores are better centered when overlaps are shorter and the kinetochore fiber flux markedly slower than the bridging fiber flux. We identify Kif18A and Kif4A as overlap and flux regulators and NuMA as a fiber coupler. Thus, length-dependent sliding forces exerted by the bridging fiber onto kinetochore fibers promote chromosome alignment. Population differences in the length and early-life dynamics of telomeres among European pied flycatchers Telomere length and shortening rate are increasingly used as biomarkers for long-term costs in ecological and evolutionary studies because of their relationships with survival and fitness. Both early-life conditions and growth, and later-life stressors can create variation in telomere shortening rate. Studies on between- population telomere length and dynamics are scarce, despite the expectation that populations exposed to varying environmental constraints would present divergent telomere length patterns. The pied flycatcher (Ficedula hypoleuca) is a passerine bird breeding across Eurasia (from Spain to western Siberia) and migrating through the Iberian Peninsula to spend the non-breeding period in sub-Saharan Africa. Thus, different populations show marked differences in migration distance. We studied the large-scale variation of telomere length and early-life dynamics in the pied flycatcher by comparing six European populations across a north- south gradient (Finland, Estonia, England, and Spain) predicting negative effect of migration distance on adult telomere length, and of nestling growth on nestling telomere dynamics. There were clear population differences in telomere length, with English birds from mid-latitudes having the longest telomeres. Telomere length did not thus show consistent latitudinal variation and was not linearly linked to differences in migration distance. Early-life telomere shortening rate tended to vary between populations. Fast growth was associated with shorter telomeres in the early life, but faster nestling growth affected telomeres more negatively in northern than southern populations. While the sources of between-population differences in telomere-related biology remain to be more intensively studied, our study illustrates the need to expand telomere studies at the between-population level. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Extended-Spectrum Beta-Lactamase andCarbapenemase-Producing prediction inKlebsiella pneumoniaebased on MALDI-TOFmass spectra Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) Mass Spectrometry (MS) is a reference method for microbial identification. Currently, machine learning techniques are used to predict Antibiotic Resistance (AR) based on MALDI-TOF data. However, current solutions need costly preprocessing steps, their reproducibility is difficult due to hyperparameter cross-validation, they do not provide interpretable results, and they do not take into account the epidemiological difference inherent to data coming from different laboratories. In this paper, we validate a multi-view heterogeneous Bayesian model (SSHIBA) for AR mechanism prediction based on MALDI-TOF MS. This novel approach allows exploiting local epidemiology differences between data sources, gets rid of preprocessing steps, is easily reproducible because hyperparameters are optimized by Bayesian inference, and provides interpretable results. To validate this model and its advantages, we present two domains of Klebsiella pneumoniae isolates: 282 samples of Hospital General Universitario Gregorio Maranon (GM) domain and 120 samples for Hospital Universitario Ramon y Cajal (RyC) domain that discriminates between Wild Type (WT), Extended-Spectrum Beta-Lactamases (ESBL)-producers and ESBL + Carbapenemases (ESBL+CP)-producers. Experimental results prove that SSHIBA outperforms state-of-the-art (SOTA) algorithms by exploiting the multi-view approach that allows it to distinguish between data domains, avoiding local epidemiological problems. Moreover, it shows that there is no need to preprocess MALDI-TOF data. Its implementation in microbiological laboratories could improve the detection of multi-drug resistant isolates, optimizing the therapeutic decision and reducing the time to obtain results of the resistance mechanism. The proposed model implementation, specifically adapted to AR prediction, and data collections are publicly available on GitHub at: github.com/alexjorguer/RMPrediction Define protein variant functions with high-complexity mutagenesis libraries and enhanced mutation detection software ASMv1.0 Open reading frame (ORF) variant libraries have advanced our ability to query the functions of a large number of variants of a protein simultaneously in a single experiment. Variant libraries targeting full-length ORFs typically consists of all possible single-amino-acid substitutions and a stop codon at each amino-acid position. Because a variant differs from the template ORF by a single codon variation, variant quantification presents the most profound challenge to this technology. Efforts such as dividing a library into sub-libraries for direct sequencing, or tag-directed subassembly are practical only for small ORFs. Our approach, however, features an enhanced variant-calling tool that processes massive shotgun sequencing data, allowing one to screen a single variant library for ORFs sized up to [~]3600 bases. The variant-calling tool detects variants reliably, and also presents variant annotations in datafiles enabling analyses that have reshaped our strategies governing library design, screen deconvolution, sequencing and sequencing data analysis. The longevity response to warm temperature is neurally controlled via the regulation of collagen genes Studies in diverse species have associated higher temperatures with shorter lifespan and lower temperatures with longer lifespan. However, the mechanisms behind these inverse effects of temperature on longevity are not well understood. Here, we demonstrate that in Caenorhabditis elegans, functional loss of NPR-8, a G protein-coupled receptor related to mammalian neuropeptide Y receptors, increases worm lifespan at 25{degrees}C but not at 20{degrees}C or 15{degrees}C, and that the lifespan increase at 25{degrees}C is regulated by the NPR-8-expressing AWB and AWC chemosensory neurons as well as AFD thermosensory neurons. RNA sequencing revealed that both warm temperature and old age profoundly alter gene expression. Further investigation uncovered that the NPR-8-dependent longevity response to warm temperature is achieved by regulating the expression of a subset of collagen genes. As elevated collagen expression is a common feature of many lifespan-extending interventions and enhanced stress resistance, collagen expression could be critical for healthy aging. A multi-state dynamic process confers mechano-adaptation to the bacterial flagellar motor Adaptation is a defining feature of living systems. The bacterial flagellar motor adapts to changes in the external mechanical environment by adding or removing torque-generating stator units. However, the molecular mechanism for mechanosensitive motor remodeling remains unclear. Here, we induced stator disassembly using electrorotation, followed by the time-dependent assembly of the individual stator units into the motor after electrorotation was terminated. From these experiments, we extracted detailed statistics of the dwell times that comprise the stochastic dynamics of the binding and unbinding of stator units. Dwell times reveal multiple timescales, indicating the existence of multiple binding states of the stator units. Based on these results, we propose a minimal model in which the stator unit can occupy four different states - two bound states with very different rates of unbinding, a diffusive unbound state, and a transiently detached state. Our minimal model quantitatively explains multiple features of the experimental data and allows us to determine the transition rates among all four states. Our experiments and modeling suggest a mechanism of mechano-adaptive remodeling of the bacterial flagellar motor in which torque generated by bound stator units controls their effective unbinding rate by modulating the transition between the two bound states. Furthermore, the binding rate of stator units with the motor has a non-monotonic dependence on the number of bound units, likely because of two counteracting effects of motor rotation on the binding process. Erythropoietin supplementation ameliorates the immunological and hematological deficiencies of lysinuric protein intolerance in mice SLC7A7 encodes for y+LAT1, a cationic amino acid transporter expressed on the basolateral membrane of epithelial cells and macrophages. Mutations in human SLC7A7 cause lysinuric protein intolerance (LPI), a rare autosomal disorder with a variety of clinical symptoms. Citrulline and a low protein diet are widely used to treat the main symptoms of LPI; however, the hematological and immunological abnormalities in LPI remain poorly understood and difficult to manage by established treatments. Here, we show that erythropoietin levels are significantly diminished in mice lacking Slc7a7, which reduces the number of erythroblast precursors, resulting in mature red blood cells with a smaller mean corpuscular volume. Ex vivo analysis demonstrated that erythrocytes from Slc7a7-deficient mice were phagocytosed more by bone marrow-derived macrophages. Gene expression analysis of sorted red pulp macrophages (RPMs) from Slc7a7-deficient mice indicated that this cell population had higher erythrophagocytic activity, but preserved heme catabolic activity. The increase in erythrophagocytosis resulted in iron accumulation in macrophages and tissues, and ultimately led to RPM apoptosis. Surprisingly, ablation of Slc7a7 in myeloid cells failed to trigger tissue iron accumulation or changes in the RPM population, indicating that the expression of this gene in macrophages is not key for the development of iron accumulation in tissue. Finally, restoration of serum erythropoietin levels in Slc7a7-deficient mice re-established normal erythropoiesis and erythrophagocytosis and prevented the accumulation of iron in tissues. Thus, erythropoietin has a fundamental role in the immune-hematological alterations of LPI in mice, revealing a new crucial role for this hormone in this disease. Structural insights into p300 regulation and acetylation-dependent genome organisation Histone modifications are deposited by chromatin modifying enzymes and read out by proteins that recognize the modified state. BRD4-NUT is an oncogenic fusion protein of the acetyl lysine reader BRD4 that binds to the acetylase p300 and enables formation of long-range intra- and interchromosomal interactions. We here examine how acetylation reading and writing enable formation of such interactions. We show that NUT contains an acidic transcriptional activation domain that binds to the TAZ2 domain of p300. We use NMR to investigate the structure of the complex and found that the TAZ2 domain has an autoinhibitory role for p300. NUT-TAZ2 interaction or mutations found in cancer that interfere with autoinhibition by TAZ2 allosterically activate p300. p300 activation results in a self-organizing, acetylation-dependent feed-forward reaction that enables long-range interactions by bromodomain multivalent acetyl-lysine binding. We discuss the implications for chromatin organisation, gene regulation and dysregulation in disease. Genetic analysis of mitochondrial DNA copy number and associated traits identifies loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation, and reveals a causal association of mitochondrial function with mortality Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses were used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 x 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 x 10-8) and mtDNA replication (p = 1.2 x 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 x 10-4).