Linked machine learning classifiers improve species classification of fungi when using error-prone long-reads on extended metabarcodes BackgroundThe increased usage of error-prone long-read sequencing for metabarcoding of fungi has not been matched with adequate public databases and concomitant analysis approaches. We address this gap and present a proof-of-concept study for classifying fungal taxa using linked machine learning classifiers. We demonstrate the capability of linked machine learning classifiers to accurately classify species and strains using real-world and simulated fungal ribosomal DNA datasets, including plant and human pathogens. We benchmark our new approach in comparison to current alignment and k-mer based methods based on synthetic mock communities. We also assess real world applications of species identification in complex unlabelled datasets.

ResultsOur machine learning approach assigned individual nanopore long-read amplicon sequences to fungal species with high recall rates and low false positive rates. Importantly, our approach successfully distinguished between closely-related species and strains when individual read errors were higher than the genetic distance between individual taxa, which the alignment and k-mer methods could not do. The machine learning approach showed an ability to identify key species with high recall rates, even in complex samples of unknown species composition.

ConclusionsA proof of concept machine learning approach using a tree-descent approach on a decision tree of classifiers can identify known taxa with high accuracy, and precisely detect known target species from complex samples with high recall rates. We propose this approach is suitable for detecting the known knowns of pathogens or invasive species in any environment of mostly unknown composition, including agriculture and wild ecosystems.
Widespread redundancy in -omics profiles of cancer mutation states In studies of cellular function in cancer, researchers are increasingly able to choose from many -omics assays as functional readouts. Choosing the correct readout for a given study can be difficult, and which layer of cellular function is most suitable to capture the relevant signal may be unclear. In this study, we consider prediction of cancer mutation status (presence or absence) from functional -omics data as a representative problem. Since functional signatures of cancer mutation have been identified across many data types, this problem presents an opportunity to quantify and compare the ability of different -omics readouts to capture signals of dysregulation in cancer. The TCGA Pan-Cancer Atlas contains genetic alteration data including somatic mutations and copy number variants (CNVs), as well as several -omics data types. From TCGA, we focus on RNA sequencing, DNA methylation arrays, reverse phase protein arrays (RPPA), microRNA, and somatic mutational signatures as -omics readouts.

Across a collection of genes recurrently mutated in cancer, RNA sequencing tends to be the most effective predictor of mutation state. Surprisingly, we found that for many of the genes we considered, one or more other data types are approximately equally effective predictors. Performance was more variable between mutations than it was between data types for the same mutation, and there was often little difference between the top data types. We also found that combining data types into a single multi-omics model provided little or no improvement in predictive ability over the best individual data type. Based on our results, for the design of studies focused on the functional outcomes of cancer mutations, there are often multiple -omics types that can serve as effective readouts, although gene expression seems to be a reasonable default option.
The neurogenic fate of the hindbrain boundaries relies on Notch-dependent asymmetric cell divisions The generation of cell diversity in the central nervous system occurs during embryogenesis and requires a precise balance between cell proliferation, commitment to specific fates, and further neuronal differentiation. The cellular and molecular mechanisms regulating this balance in the embryonic brain are still poorly understood. Here we study how the neurogenic capacity in the embryonic hindbrain is spatiotemporally allocated, and how the fate and the growth of the hindbrain boundary cells are regulated. By generating a CRISPR-based knock-in zebrafish transgenic line to specifically label the hindbrain boundaries, we unveiled that boundary cells undergo a functional transition to become neurogenic during hindbrain segmentation concurrently as they maintain the progenitor cell pool. Boundary cells engaged in neurogenesis coinciding with the onset of Notch signaling, which triggered their asymmetrical cell division. Our findings reveal that distinct neurogenic phases take place during hindbrain growth and suggest that boundary cells contribute to refine the final number, identity, and proportion of neurons in the brain.

SUMMARYHindbrain boundary cells undergo a functional transition to become neurogenic concurrently as they are maintained as a progenitor cell pool. This involves a behavioral switch from symmetrically dividing progenitor cells to asymmetrically dividing progenitors, which depends on Notch-activity. An integrative approach leads to the discovery of a novel anti-leukemic peptide from human milk Chemotherapy in childhood leukemia is associated with late morbidity in leukemic survivors, while certain patient subsets are relatively resistant to standard chemotherapy. It is therefore important to identify new agents with sensitivity and selectivity towards leukemic cells, while having less systemic toxicity. Peptide-based therapeutics has gained much attention during the last few years. Here, we used an integrative workflow combining mass spectrometric peptide library construction, in silico anticancer peptide screening, and in vitro leukemic cell studies to discover a novel anti-leukemic peptide having 3+charges and alpha-helical structure, namely HMP-S7, from human breast milk. HMP-S7 showed cytotoxic activity against four distinct leukemic cell lines in a dose-dependent manner but had no effect on solid malignancies or representative normal cells. HMP-S7 induced leukemic cell death by penetrating the plasma membrane to enter the cytoplasm and cause leakage of lactate dehydrogenase, thus acting in a membranolytic manner. Importantly, HMP-S7 exhibited anti-leukemic effect against patient-derived leukemic cells ex vivo. In conclusion, HMP-S7 is a selective anti-leukemic peptide with promise which requires further validation in preclinical and clinical studies.

TeaserIn silico screening of naturally occurring human milk peptides discovers a new anticancer peptide that kills leukemic cells in vitro and ex vivo. Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2 Back and forth transmission of SARS-CoV-2 between humans and animals may lead to wild reservoirs of virus that can endanger efforts toward long-term control of COVID-19 in people, and protecting vulnerable animal populations that are particularly susceptible to lethal disease. Predicting high risk host species is key to targeting field surveillance and lab experiments that validate host zoonotic potential. A major bottleneck to predicting animal hosts is the small number of species with available molecular information about the structure of ACE2, a key cellular receptor required for viral cell entry. We overcome this bottleneck by combining species ecological and biological traits with 3D modeling of virus and host cell protein interactions using machine learning methods. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for over 5,000 mammals -- an order of magnitude more species than previously possible. The high accuracy predictions achieved by this approach are strongly corroborated by in vivo empirical studies. We identify numerous common mammal species whose predicted zoonotic capacity and close proximity to humans may further enhance the risk of spillover and spillback transmission of SARS-CoV-2. Our results reveal high priority areas of geographic overlap between global COVID-19 hotspots and potential new mammal hosts of SARS-CoV-2. With molecular sequence data available for only a small fraction of potential host species, predictive modeling integrating data across multiple biological scales offers a conceptual advance that may expand our predictive capacity for zoonotic viruses with similarly unknown and potentially broad host ranges. Characterising ontogeny of numerosity discrimination in zebrafish reveals the use of multiple, numerical and non- numerical mechanisms. A sense of non-symbolic numerical magnitudes is widespread in the animal kingdom and has been documented in adult zebrafish. Here we investigated the ontogeny of this ability using a group size preference task in juvenile zebrafish. Fish showed group size preference from 21 days post fertilization (dpf) and reliably chose the larger group when presented with discriminations of between 1 vs. 3, 2 vs. 5 and 2 vs. 3 conspecifics but not 2 vs. 4 conspecifics. When the ratio between the number of conspecifics in each group was maintained at 1:2, fish could discriminate between 1 vs. 2 individuals and 3 vs. 6, but again, not when given a choice between 2 vs. 4 individuals. These findings are in agreement with studies in other species suggesting the systems involved in quantity representation do not operate separately from other cognitive mechanisms. Rather they suggest quantity processing in fish may be the result of an interplay between attentional, cognitive and memory-related mechanisms as in humans and other animals. Our results emphasise the potential of the use of zebrafish to explore the genetic and neural processes underlying the ontogeny and function of number cognition. 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. The impact of housing conditions on mesenchymal stromal/stem cell populations differ between adipose tissue and skeletal muscle BackgroundIn pigs, the ratio between lean mass and fat mass in the carcass determines production efficiency and is strongly influenced by the number and size of cells in tissues. During growth, the increase in the number of cells results from the recruitment of different populations of multipotent mesenchymal stromal/stem cells (MSCs) residing in the tissues. We hypothesized that the impact of hygiene of housing conditions during growth on the proportions of MSCs in adipose tissue and skeletal muscle may differ between pigs with different residual feed intake (RFI), a measure of feed efficiency.

MethodsAt the age of 12 weeks, Large White pigs from two lines divergently selected for low and high RFI were housed in two contrasting hygiene conditions (good vs poor). After six weeks, pigs were slaughtered (n = 30; 5-9/group). Samples of subcutaneous adipose tissue and longissimus skeletal muscle were collected, and cells from the stromal vascular fraction (SVF), which includes mesenchymal stromal/stem cell populations, were isolated from each tissue. Adipose and muscle cell populations from the SVF were phenotyped by flow cytometry using antibodies that targeted different cell surface markers (CD45 to separate hematopoietic cells from MSCs; CD34, CD38, CD56 and CD140a to identify MSC populations with adipogenic and/or myogenic potential).

ResultsAdipose tissue and muscle shared some common MSC populations although MSC diversity was higher in muscle than in adipose tissue. In muscle, the CD45-CD56+CD34-CD140a+ and CD45-CD56+CD34+CD140a+ cell populations were abundant. Of these two cell populations, only the proportions of CD45-CD56+CD34+CD140a+ cells increased (P < 0.05) in pigs housed in poor hygiene as compared with pigs in good hygiene conditions. For the CD45-CD56-CD34- cell population, present in low proportion, there was an interaction between hygiene condition and genetic line (P < 0.05) with a decrease in low RFI pigs housed in poor hygiene conditions. In adipose tissue, the two abundant MSC populations were CD45-CD56-CD34- and CD45-CD56+CD34-. The proportion of CD45-CD56-CD34- cells increased (P < 0.05) whereas the proportion of CD45-CD56+CD34- tended to decrease (P < 0.1) in pigs housed in poor conditions. This study shows that the proportions of some MSC populations were affected by hygiene of housing conditions in a tissue-dependent manner in pigs of both RFI lines. It suggests that MSCs may play a significant role in adipose tissue and skeletal muscle homeostasis and may influence later growth and body composition in growing animals. Expression and subcellular localization of USH1C/harmonin in the human retina provides insights into pathophysiology and therapy of Usher syndrome Usher syndrome (USH) is the most common form of hereditary deafness-blindness in humans. USH is a complex genetic disorder, assigned to three clinical subtypes differing in onset, course and severity, with USH1 being the most severe. Rodent USH1 models do not reflect the ocular phenotype observed in human patients to date; hence, little is known about the pathophysiology of USH1 in the human eye. One of the USH1 genes, USH1C, exhibits extensive alternative splicing and encodes numerous harmonin protein isoforms that function as scaffolds for organizing the USH interactome. RNA-seq analysis of human retina uncovered harmonin a1 as the most abundant transcript of USH1C. Bulk RNA-seq analysis and immunoblotting showed abundant expression of harmonin in Muller glia cells (MGCs) and retinal neurons. Furthermore, harmonin was localized in the terminal endfeet and apical microvilli of MGCs, presynaptic region (pedicle) of cones, and outer segments of rods as well as at adhesive junctions of MGCs and photoreceptors in the outer limiting membrane (OLM). Our data provide evidence for the interaction of harmonin with OLM molecules in MGCs and photoreceptors and rhodopsin in photoreceptors. Subcellular expression and colocalization of harmonin correlates with the clinical phenotype observed in USH1C patients. In addition, primary cilia defects in USH1C patient-derived fibroblasts could be reverted by delivery of harmonin a1 transcript isoform. Our data provide novel insights into photoreceptor cell biology, USH1C pathophysiology and for developing gene therapy treatment. Collective dynamics in the presence of finite-width pulses The idealisation of neuronal pulses as{delta} -spikes is a convenient approach in neuroscience but can sometimes lead to erroneous conclusions. We investigate the effect of a finite pulse-width on the dynamics of balanced neuronal networks. In particular, we study two populations of identical excitatory and inhibitory neurons in a random network of phase oscillators coupled through exponential pulses with different widths. We consider three coupling functions, inspired by leaky integrate-and-fire neurons with delay and type-I phase-response curves. By exploring the role of the pulse-widths for different coupling strengths we find a robust collective irregular dynamics, which collapses onto a fully synchronous regime if the inhibitory pulses are sufficiently wider than the excitatory ones. The transition to synchrony is accompanied by hysteretic phenomena (i.e. the co-existence of collective irregular and synchronous dynamics). Our numerical results are supported by a detailed scaling and stability analysis of the fully synchronous solution. A conjectured first-order phase transition emerging for{delta} -spikes is smoothed out for finite-width pulses. Selective Ablation of 3' RNA ends and Processive RTs Facilitate Direct cDNA Sequencing of Full-length Host Cell and Viral Transcripts Alternative splicing (AS) is necessary for viral proliferation in host cells and a critical regulatory component of viral gene expression. Conventional RNA-seq approaches provide incomplete coverage of AS due to their short read-lengths and are susceptible to biases and artifacts introduced in prevailing library preparation methodologies. Moreover, viral splicing studies are often conducted separately from host cell transcriptome analysis, precluding an assessment of the viral manipulation of host splicing machinery. To address current limitations, we developed a quantitative full-length direct cDNA sequencing strategy to simultaneously profile viral and host cell transcripts. This nanopore-based approach couples processive reverse transcriptases with a novel one-step chemical ablation of 3 RNA ends (termed CASPR) which decreases ribosomal RNA reads and enriches for poly-adenylated coding sequences. We extensively validate our approach using synthetic reference transcripts and show CASPR doubles the breadth of coverage per transcript and increases detection of long transcripts (>4kb), while being functionally equivalent to PolyA+ selection for transcript quantification. We used our approach to interrogate host cell and HIV-1 transcript dynamics during viral reactivation and identified novel putative HIV-1 host factors containing exon skipping or novel intron retentions and delineated the HIV-1 transcriptional state associated with these differentially regulated host factors. The biochemical resolving power of fluorescence lifetime imaging: untangling the roles of the instrument response function and photon-statistics A deeper understanding of spatial resolution has led to innovations in microscopy and the disruption of biomedical research, as with super-resolution microscopy. To foster similar advances in time-resolved and spectral imaging, we have previously introduced the concept of  biochemical resolving power in fluorescence microscopy. Here, we apply those concepts to investigate how the instrument response function (IRF), sampling conditions, and photon-statistics limit the biochemical resolution of fluorescence lifetime microscopy. Using Fisher information analysis and Monte Carlo simulations, we reveal the complex dependencies between photon-statistics and the IRF, permitting us to quantify resolution limits that have been poorly understood (e.g., the minimum resolvable decay time for a given width of the IRF and photon-statistics) or previously underappreciated (e.g., optimization of the IRF for biochemical detection). With this work, we unravel common misunderstandings on the role of the IRF and provide theoretical insights with significant practical implications on the design and use of time-resolved instrumentation. Genome-wide association study suggests an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels Despite being one of the most consumed vegetables in the United States, the elemental profile of sweet corn (Zea mays L.) is limited in its dietary contributions. To address this through genetic improvement, a genome-wide association study was conducted for the concentrations of 15 elements in fresh kernels of a sweet corn association panel. In concordance with mapping results from mature maize kernels, we detected a probable pleiotropic association of zinc and iron concentrations with nicotianamine synthase5 (nas5), which purportedly encodes an enzyme involved in synthesis of the metal chelator nicotianamine. Additionally, a pervasive association signal was identified for cadmium concentration within a recombination suppressed region on chromosome 2. The likely causal gene underlying this signal was heavy metal ATPase3 (hma3), whose counterpart in rice, OsHMA3, mediates vacuolar sequestration of cadmium and zinc in roots, whereby regulating zinc homeostasis and cadmium accumulation in grains. In our association panel, hma3 associated with cadmium but not zinc accumulation in fresh kernels. This finding implies that selection for low cadmium will not affect zinc levels in fresh kernels. Although less resolved association signals were detected for boron, nickel, and calcium, all 15 elements were shown to have moderate predictive abilities via whole-genome prediction. Collectively, these results help enhance our genomics-assisted breeding efforts centered on improving the elemental profile of fresh sweet corn kernels. Neuroinvasion and neurotropism by SARS-CoV-2 variants in the K18-hACE2 mouse Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) not only affects the respiratory tract but also causes neurological symptoms such as loss of smell and taste, headache, fatigue or severe cerebrovascular complications. Using transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) we investigated the spatiotemporal distribution and pathomorphological features in the CNS following intranasal infection with SARS-CoV-2 variants, also after prior influenza A virus infection. Apart from Omicron, we found all variants to frequently spread to and within the CNS. Infection was restricted to neurons and appeared to spread from the olfactory bulb mainly in basally orientated regions in the brain and into the spinal cord, independent of ACE2 expression and without evidence of neuronal cell death, axonal damage or demyelination. However, microglial activation, microgliosis and a mild macrophage and T cell dominated inflammatory response was consistently observed, accompanied by apoptotic death of endothelial, microglial and immune cells, without their apparent infection. Microgliosis and immune cell apoptosis indicate a potential role of microglia for pathogenesis and viral effect in COVID-19 and possible impairment of neurological functions, especially in long COVID. These data may also be informative for the selection of therapeutic candidates, and broadly support investigation of agents with adequate penetration into relevant regions of the CNS. Climate change and chill accumulation: implications for tree fruit production in cold-winter regions Winter chill accumulation is critical for the productivity and profitability of perennial tree fruit systems. Several studies have quantified the impacts of global warming on chill accumulation in the warmer production regions of the world, where insufficient chill events occur and their frequency is increasing. In contrast, we focus on a region with relatively cold winters-the Pacific Northwest United States (PNW)-where insufficient chill events are currently absent, and quantify the potential for introduction of these risks under climate change. Results identified spatial variation within the PNW, with chill accumulation projected to increase in some areas but decrease in others. There was also spatiotemporal variation in the driving factors of changes to chill accumulation. Even with decreases in chill accumulations, there are likely minimal issues with insufficient chill accumulation. However, delayed chill accumulation in combination with advances in the onset of heat accumulation can potentially shift the region from one where spring phenology is primarily forcing-driven to one where the dynamic interplay between chilling and forcing processes become important. These interactions might create production risks for varieties with high chill requirements, post mid-21st-century under high emissions scenarios. Future work should focus on understanding, modeling, and projecting responses across these overlapping chilling and forcing processes. Additionally, given significant spatial differences across a relatively small geographic range, it is also critical to understand and model these dynamics at a local landscape resolution for regions such as the PNW. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. A bacterial extracellular vesicle-based intranasal vaccine against SARS-CoV-2 protects against disease and elicits neutralizing antibodies to wild-type virus and Delta variant Several vaccines have been introduced to combat the coronavirus infectious disease-2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current SARS-CoV-2 vaccines include mRNA-containing lipid nanoparticles or adenoviral vectors that encode the SARS-CoV-2 Spike (S) protein of SARS-CoV-2, inactivated virus, or protein subunits. Despite growing success in worldwide vaccination efforts, additional capabilities may be needed in the future to address issues such as stability and storage requirements, need for vaccine boosters, desirability of different routes of administration, and emergence of SARS-CoV-2 variants such as the Delta variant. Here, we present a novel, well-characterized SARS-CoV-2 vaccine candidate based on extracellular vesicles (EVs) of Salmonella typhimurium that are decorated with the mammalian cell culture-derived Spike receptor-binding domain (RBD). RBD-conjugated outer membrane vesicles (RBD-OMVs) were used to immunize the golden Syrian hamster (Mesocricetus auratus) model of COVID-19. Intranasal immunization resulted in high titers of blood anti-RBD IgG as well as detectable mucosal responses. Neutralizing antibody activity against wild-type and Delta variants was evident in all vaccinated subjects. Upon challenge with live virus, hamsters immunized with RBD-OMV, but not animals immunized with unconjugated OMVs or a vehicle control, avoided body mass loss, had lower virus titers in bronchoalveolar lavage fluid, and experienced less severe lung pathology. Our results emphasize the value and versatility of OMV-based vaccine approaches. 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. Stress-dependent cell stiffening by tardigrade tolerance proteins through reversible formation of cytoskeleton-like filamentous network and gel-transition Tardigrades are able to tolerate almost complete dehydration by entering a reversible ametabolic state called anhydrobiosis and resume their animation upon rehydration. Dehydrated tardigrades are exceptionally stable and withstand various physical extremes. Although trehalose and late embryogenesis abundant (LEA) proteins have been extensively studied as potent protectants against dehydration in other anhydrobiotic organisms, tardigrades produce high amounts of tardigrade-unique protective proteins. Cytoplasmic-abundant heat-soluble (CAHS) proteins are uniquely invented in the lineage of eutardigrades, a major class of the phylum Tardigrada and are essential for their anhydrobiotic survival. However, the precise mechanisms of their action in this protective role are not fully understood. In the present study, we first postulated the presence of tolerance proteins that form protective condensates via phase separation in a stress-dependent manner and searched for tardigrade proteins that reversibly form condensates upon dehydration-like stress. Through comprehensive analysis, we identified 336 such proteins, collectively dubbed "Desolvataion-induced ReversiblY condensing Proteins (DRYPs)". Unexpectedly, we rediscovered CAHS proteins as highly enriched in DRYPs, 3 of which were major components of DRYPs. We revealed that these CAHS proteins reversibly polymerize into many cytoskeleton-like filaments depending on hyperosmotic stress in cultured cells and undergo reversible gel-transition in vitro. CAHS filamentation increases cell stiffness to resist deformation and improves resistance to dehydration-like stress. The conserved putative helical C-terminal region is necessary and sufficient for filament formation by CAHS proteins, and mutations disrupting the secondary structure of this region impaired both the filament formation and the gel transition. On the basis of these results, we propose that CAHS proteins are novel cytoskeletal proteins that form filamentous networks and undergo gel-transition in a stress-dependent manner to provide on-demand physical stabilization of cell integrity against deformative forces during dehydration and also contribute to the exceptional physical stability in a dehydrated state. Insertions in SARS-CoV-2 genome caused by template switch and duplications give rise to new variants that merit monitoring The appearance of multiple new SARS-CoV-2 variants during the winter of 2020-2021 is a matter of grave concern. Some of these new variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the COVID-19 pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on point nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the spike protein is thought to be a determinant of SARS-CoV-2 virulence and other inserts might have contributed to coronavirus pathogenicity as well. Here, we investigate insertions in SARS-CoV-2 genomes and identify 347 unique inserts of different lengths. We present evidence that these inserts reflect actual virus variance rather than sequencing errors. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. We show that inserts in the Spike glycoprotein can affect its antigenic properties and thus merit monitoring. At least, three inserts in the N-terminal domain of the Spike (ins245IME, ins246DSWG, and ins248SSLT) that were first detected in 2021 are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity. Regulation of DNA damage response by trimeric G-protein Signaling Upon sensing DNA double-strand breaks (DSBs), eukaryotic cells either die or repair DSBs via one of two competing pathways, i.e., non-homologous end-joining (NHEJ) or homologous recombination (HR). We show that cell fate after DNA damage hinges on the guanine nucleotide-exchange modulator of heterotrimeric G-protein, Gi*{beta}{gamma}, GIV/Girdin. GIV suppresses HR by binding and sequestering BRCA1, a key coordinator of multiple steps within the HR pathway, away from DSBs; it does so using a C-terminal motif that binds BRCA1s BRCT-modules via both phospho-dependent and -independent mechanisms. GIV promotes NHEJ, and binds and activates Gi and enhances the  free G{beta}{gamma}[-&gt;]PI-3-kinase[-&gt;]Akt pathway, thus revealing the enigmatic origin of prosurvival Akt signals during dsDNA repair. Absence of GIV, or the loss of either of its two functions impaired DNA repair, and induced cell death when challenged with numerous cytotoxic agents. That GIV selectively binds few other BRCT-containing proteins suggests convergent signaling such that heterotrimeric G-proteins may finetune sensing, repair, and outcome after DNA damage.

GRAPHIC ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/452842v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@3d5202org.highwire.dtl.DTLVardef@1d32d89org.highwire.dtl.DTLVardef@152a85dorg.highwire.dtl.DTLVardef@1ab9953_HPS_FORMAT_FIGEXP  M_FIG C_FIG HIGHLIGHTSO_LINon-receptor G protein modulator, GIV/Girdin binds BRCA1
C_LIO_LIBinding occurs in both canonical and non-canonical modes
C_LIO_LIGIV sequesters BRCA1 away from dsDNA breaks, suppresses HR
C_LIO_LIActivation of Gi by GIV enhances Akt signals, favors NHEJ
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IN BRIEFIn this work, the authors show that heterotrimeric G protein signaling that is triggered by non-receptor GEF, GIV/Girdin, in response to double-stranded DNA breaks is critical for decisive signaling events which favor non-homologous end-joining (NHEJ) and inhibit homologous recombination (HR). A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. Immunomodulatory Contribution of Mast Cells to the Regenerative Biomaterial Microenvironment Bioactive immunomodulatory biomaterials have shown promise for influencing the immune response to promote tissue repair and regeneration. Macrophages and T cells have been associated with this response; however, other immune cell types have been traditionally overlooked. In this study, we investigated the role of mast cells in the regulation of the immune response to decellularized biomaterial scaffolds using a subcutaneous implant model. In mast cell-deficient mice, there was dysregulation of the expected M1 to M2 macrophage transition typically induced by the biomaterial scaffold. Polarization progression deviated in a sex specific manner with an early transition to an M2 profile in female mice, while the male response was unable to properly transition past a pro-inflammatory M1 state. Both were reversed with adoptive mast cell transfer. Further investigation of the later stage immune response in male mice determined a greater sustained pro-inflammatory gene expression profile including the IL-1 cytokine family, IL-6, alarmins, and chemokines. These results highlight mast cells as another important cell type that influences the immune response to pro-regenerative biomaterials. Electrical Stimulated GLUT4 Signaling Attenuates Critical Illness-Associated Muscle Wasting BackgroundCritical illness myopathy (CIM) is a debilitating condition characterized by the preferential loss of the motor protein myosin. CIM is a byproduct of critical care, attributed to impaired recovery, long-term complications, and mortality. CIM pathophysiology is complex, heterogeneous and remains incompletely understood, however loss of mechanical stimuli contributes to critical illness associated muscle atrophy and weakness. Passive mechanical loading (ML) and electrical stimulation (ES) therapies augment muscle mass and function. While having beneficial outcomes, the mechanistic underpinning of these therapies is less known. Therefore, here we aimed to assess the mechanism by which chronic supramaximal ES ameliorates CIM in a unique experimental rat model of critical care.

MethodsRats were subjected to 8 days critical care conditions entailing deep sedation, controlled mechanical ventilation, and immobilization with and without direct soleus ES. Muscle size and function were assessed at the single cell level. RNAseq and Western blotting were employed to understand the mechanisms driving ES muscle outcomes in CIM.

ResultsFollowing 8 days of controlled mechanical ventilation and immobilization, soleus muscle mass, Myosin:Actin ratio and single muscle fiber maximum force normalized to cross-sectional area (specific force) were reduced by 40-50% (p< 0.0001). ES significantly reduced the loss of soleus muscle fiber cross-sectional area (CSA) and Myosin:Actin ratio by approximately 30% (p< 0.05) yet failed to effect specific force. RNAseq pathway analysis revealed downregulation of insulin signaling in the soleus muscle following critical care and GLUT4 trafficking was reduced by 55% leading to an 85% reduction of muscle glycogen content (p< 0.01). ES promoted phosphofructokinase and insulin signaling pathways to control levels (p< 0.05), consistent with the maintenance of GLUT4 translocation and glycogen levels. AMPK, but not AKT, signaling pathway was stimulated following ES, where the downstream target TBC1D4 increased 3 logFC (p= 0.029) and AMPK-specific P-TBC1D4 levels were increased approximately 2-fold (p= 0.06). Reduction of muscle protein degradation rather than protein synthesis promoted soleus CSA, as ES reduced E3 ubiquitin proteins, Atrogin-1 (p= 0.006) and MuRF1 (p= 0.08) by approximately 50%, downstream of AMPK-FoxO3.

ConclusionsES maintained GLUT4 translocation through increased AMPK-TBC1D4 signaling leading to improved muscle glucose homeostasis. Soleus CSA and myosin content was promoted through reduced protein degradation via AMPK-FoxO3 E3 ligases, Atrogin-1 and MuRF1. These results demonstrate chronic supramaximal ES reduces critical care associated muscle wasting, preserved glucose signaling and reduced muscle protein degradation in CIM. Essential Regression - a generalizable framework for inferring causal latent factors from multi-omic human datasets High-dimensional cellular and molecular profiling of human samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate predictive biomarkers and prioritized causal inferences. Current methods are limited by high dimensionality of the combined datasets, the differences in their data distributions and their integration to infer causal relationships. Here we present Essential Regression (ER), an interpretable machine learning approach for high-dimensional multi-omic datasets, that addresses these problems by identifying latent factors and their likely cause-effect relationships with the system-wide outcome/properties of interest. ER is a novel data-distribution-free latent-factor regression model that integrates multi-omic datasets and identifies latent factors significantly associated with an outcome. ER outperforms a range of state-of-the-art methods in terms of prediction performance on simulated datasets. ER can be coupled with probabilistic graphical modeling thereby strengthening the causal inferences. ER generates novel cellular and molecular predictions, using multi-omic human systems immunology datasets, pertaining to immunosenescence and immune dysregulation. A distinct brain expression profile for genes within large introgression deserts and under positive selection in Homo sapiens Analyses of ancient DNA from extinct hominins have provided unique insights into the complex evolutionary history of Homo sapiens, intricately related to that of the Neanderthals and the Denisovans as revealed by several instances of admixture events. These analyses have also allowed the identification of introgression deserts: genomic regions in our species that are depleted of  archaic haplotypes. The presence of genes like FOXP2 in these deserts has been taken to be suggestive of brain-related functional differences between Homo species. Here, we seek a deeper characterization of these regions, taking into account signals of positive selection in our lineage. Analyzing publicly available transcriptomic data from the human brain at different developmental stages, we found that structures outside the cerebral neocortex, in particular the cerebellum, the striatum and the mediodorsal nucleus of the thalamus show the most divergent transcriptomic profiles when considering genes within large introgression deserts and under positive selection.