Miracle-dz/UniFAR-FTUs huggingface dataset:
Ndr/Lats kinases bind specific Mob-family coactivators through a conserved and modular interface.

Ndr/Lats kinases bind Mob coactivator proteins to form complexes that are essential and deeply conserved components of "Hippo" signaling pathways, which control cell proliferation and morphogenesis in eukaryotes. All Ndr/Lats kinases have a characteristic N-terminal region NTR that binds a specific Mob co-factor: Lats kinases associate with Mob1 proteins, and Ndr kinases associate with Mob2 proteins. To better understand the significance of Mob protein association with Ndr/Lats kinases and selective binding of Ndr and Lats to distinct Mob co-factors, we solved crystal structures of Saccharomyces cerevisiae Cbk1NTR-Mob2 and Dbf2NTR-Mob1 and experimentally assessed determinants of Mob cofactor binding and specificity. This allowed significant refinement of the previously determined structure of Cbk1 kinase bound to Mob2, presently the only crystallographic model of a full length Ndr/Lats kinase complexed with a Mob cofactor. Our analysis indicates that the Ndr/LatsNTR-Mob interface provides a distinctive kinase regulation mechanism, in which Mob co-factor organizes the Ndr/Lats NTR to interact with the AGC kinase C-terminal hydrophobic motif (HM) activation segment. The Mob-organized NTR appears to mediate HM association with an allosteric site on the kinase N lobe. We also found that Cbk1 and Dbf2 associated specifically with Mob2 and Mob1, respectively. Alteration of residues in the Cbk1 NTR allows association of non-cognate Mob co-factor, indicating that cofactor specificity is restricted by discrete sites rather than broadly distributed. Overall, our analysis provides a new picture of the functional role of Mob association, and indicates that the Ndr/LatsNTR-Mob interface is largely a common structural platform that mediates kinase-cofactor binding.
LSTrAP-Cloud: A User-friendly Cloud Computing Pipeline to Infer Co-functional and Regulatory Networks

As genomes become more and more available, gene function prediction presents itself as one of the major hurdles in our quest to extract meaningful information on the biological processes genes participate in. In order to facilitate gene function prediction, we show how our user-friendly pipeline, Large-Scale Transcriptomic Analysis Pipeline in Cloud (LSTrAP-Cloud), can be useful in helping biologists make a shortlist of genes that they might be interested in. LSTrAP-Cloud is based on Google Colaboratory and provides user-friendly tools that process and quality-control RNA sequencing data streamed from the European Sequencing Archive. LSTRAP-Cloud outputs a gene co-expression network that can be used to identify functionally related genes for any organism with a sequenced genome and publicly available RNA sequencing data. Here, we used the biosynthesis pathway of Nicotiana tabacum as a case study to demonstrate how enzymes, transporters and transcription factors involved in the synthesis, transport and regulation of nicotine can be identified using our pipeline.
Evidence for a biological source of widespread, reproducible nighttime oxygen spikes in tropical reef ecosystems has implications for coral health

Primary producers release oxygen as the by-product of photosynthetic light reactions during the day. However, a prevalent, globally-occurring nighttime spike in dissolved oxygen in the absence of light challenges the traditional assumption that biological oxygen production is limited to daylight hours, particularly in tropical coral reefs. Here we show: 1) the widespread nature of this phenomenon, 2) its reproducibility across tropical marine ecosystems, 3) the influence of biotic and abiotic factors on this phenomenon across numerous datasets, and 4) the observation of nighttime oxygen spikes in vitro from incubations of coral reef benthic organisms. The data from this study demonstrate that in addition to physical forcing, biological processes are likely responsible for increasing dissolved oxygen at night. Additionally, we demonstrate an association between these nighttime oxygen spikes and measures of both net community calcification and net community production. These results suggest that nighttime oxygen spikes are likely a biological response associated with increased respiration and are most prominent in communities dominated by calcifying organisms.
Sensitive cells extend antibiotic-driven containment of drug-resistant bacterial populations

Treatment strategies for infectious disease often aim to rapidly clear the pathogen population in hopes of minimizing the potential for antibiotic resistance. However, a number of recent studies highlight the potential of alternative strategies that attempt to inhibit the growth of resistant pathogens by maintaining a competing population of drug-sensitive cells. Unfortunately, to date there is little direct experimental evidence that drug sensitive cells can be leveraged to enhance antibiotic containment strategies. In this work, we combine in vitro experiments in computer-controlled bioreactors with simple mathematical models to show that drug-sensitive cells can enhance our ability to control bacterial populations with antibiotics. To do so, we measured the “escape time” required for drug-resistant E. coli populations to eclipse a threshold density maintained by adaptive antibiotic dosing. While populations containing only resistant cells rapidly escape containment, we found that matched populations with sensitive cells added could be contained for significantly longer. The increase in escape time occurs only when the threshold density–the acceptable bacterial burden–is sufficiently high, an effect that mathematical models attribute to increased competition. The results provide direct experimental evidence linking the presence of sensitive cells to improved control of microbial populations.
A causal role for the pulvinar in coordinating task‐independent cortico–cortical interactions

The pulvinar is the largest nucleus in the primate thalamus and has topographically organized connections with multiple cortical areas, thereby forming extensive cortico‐pulvino‐cortical input–output loops. Neurophysiological studies have suggested a role for these transthalamic pathways in regulating information transmission between cortical areas. However, evidence for a causal role of the pulvinar in regulating cortico–cortical interactions is sparse and it is not known whether pulvinar's influences on cortical networks are task‐dependent or, alternatively, reflect more basic large‐scale network properties that maintain functional connectivity across networks regardless of active task demands. In the current study, under passive viewing conditions, we conducted simultaneous electrophysiological recordings from ventral (area V4) and dorsal (lateral intraparietal area [LIP]) nodes of macaque visual system, while reversibly inactivating the dorsal part of the lateral pulvinar (dPL), which shares common anatomical connectivity with V4 and LIP, to probe a causal role of the pulvinar. Our results show a significant reduction in local field potential phase coherence between LIP and V4 in low frequencies (4–15 Hz) following muscimol injection into dPL. At the local level, no significant changes in firing rates or LFP power were observed in LIP or in V4 following dPL inactivation. Synchronization between pulvinar spikes and cortical LFP phase decreased in low frequencies (4–15 Hz) both in LIP and V4, while the low frequency synchronization between LIP spikes and pulvinar phase increased. These results indicate a causal role for pulvinar in synchronizing neural activity between interconnected cortical nodes of a large‐scale network, even in the absence of an active task state.
Evolution of an enzyme conformational ensemble guides design of an efficient biocatalyst

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we used room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 160 M−1s−1). We observed that catalytic residues were increasingly rigidified, the active site became better pre-organized, and its entrance was widened. Based on these observations, we engineered HG4, an efficient biocatalyst (kcat/KM 120,000 M−1s−1) containing active-site mutations found during evolution but not distal ones. HG4 structures revealed that its active site was pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.
Molecular identification of sixty-three amacrine cell types completes a mouse retinal cell atlas

Amacrine cells (ACs) are a diverse class of interneurons that modulate input from photoreceptors to retinal ganglion cells (RGCs), rendering each RGC type selectively sensitive to particular visual features, which are then relayed to the brain. While many AC types have been identified morphologically and physiologically, they have not been comprehensively classified or molecularly characterized. We used high-throughput single-cell RNA sequencing (scRNA-seq) to profile >32,000 ACs from mouse retina, and applied computational methods to identify 63 AC types. We identified molecular markers for each type, and used them to characterize the morphology of multiple types. We show that they include nearly all previously known AC types as well as many that had not been described. Consistent with previous studies, most of the AC types express markers for the canonical inhibitory neurotransmitters GABA or glycine, but several express neither or both. In addition, many express one or more neuropeptides, and two express glutamatergic markers. We also explored transcriptomic relationships among AC types and identified transcription factors expressed by individual or multiple closely related types. Noteworthy among these were Meis2 and Tcf4, expressed by most GABAergic and most glycinergic types, respectively. Together, these results provide a foundation for developmental and functional studies of ACs, as well as means for genetically accessing them. Along with previous molecular, physiological and morphological analyses, they establish the existence of at least 130 neuronal types and nearly 140 cell types in mouse retina. SIGNIFICANCE STATEMENT The mouse retina is a leading model for analyzing the development, structure, function and pathology of neural circuits. A complete molecular atlas of retinal cell types provides an important foundation for these studies. We used high-throughput single-cell RNA sequencing (scRNA-seq) to characterize the most heterogeneous class of retinal interneurons, amacrine cells, identifying 63 distinct types. The atlas includes types identified previously as well as many novel types. We provide evidence for use of multiple neurotransmitters and neuropeptides and identify transcription factors expressed by groups of closely related types. Combining these results with those obtained previously, we proposed that the mouse retina contains 130 neuronal types, and is therefore comparable in complexity to other regions of the brain.
A spiral attractor network drives locomotion in Aplysia

The neural control of motor behaviour arises from the joint activity of large neuron populations. Unknown is what underlying dynamical system generates this joint activity. Here we show that the network-wide activity driving locomotion of the sea-slug Aplysia is a low-dimensional spiral attractor. We imaged large populations at singlespike resolution from the Aplysia’s pedal ganglion during fictive locomotion. Evoking locomotion rapidly moved the population activity from irregular spontaneous activity into a low-dimensional, periodic, decaying, orbit. This orbit was a true attractor: the activity returned to the same orbit after transient perturbation; and repeatedly evoking locomotion caused the activity to converge on the same low-dimensional orbit. To show this attractor was the locomotion program, we accurately decoded simultaneous recordings of neck motorneuron activity directly from the low-dimensional orbit. Our results provide direct evidence that neural circuits are periodic attractors. Consequently, they support the long-held hypothesis that population activity is an emergent property of a simpler underlying system. Neural control of motor behaviour arises from the mass action of neuron populations1–6. While individual neuron activity can correlate with specific aspects of movement7,8, the intermittent participation of individual neurons across repeated movements9–12 suggests that only the collective population activity, and not specifics of single neuron firing, are key to motor control. Thus, a parsimonious theory of motor control requires unravelling the underlying system embodied by a population13–18. The idea that high-dimensional population activity is an emergent property of an underlying low-dimensional dynamical system has a long history in neural theory19,20. A key hypothesis is that stable repetitions of population activity arise from an underlying, low-dimensional attractor. Stable repetitions of low-dimensional population activity have been described in arm movements15,16, navigation systems21,22, and sensory encoding23,24, but the underlying dynamical system has not been determined. It is thus unknown whether high-dimensional population activity can emerge from a true low-dimensional attractor.
Meta-analysis of liver transcriptomic data to identify mammalian functional orthologs

Identifying which orthologs share functions from sequence alone can be challenging, notably in case of paralogous genes families. We hypothesised that co-expression network will help predict functional orthologs amongst complex homologous gene families. To explore the use of transcriptomic data available in public domain to predict functionally equivalent orthologs, we collected genome wide expression data in mouse and rat liver from over 1500 experiments with varied treatments. We used a hyper-graph clustering method to identify clusters of orthologous genes co-expressed in both mouse and rat. We validated these clusters by analysing expression proﬁles in each species separately, and demonstrating a high overlap. We then focused on genes in 18 homology groups with one-to-many or many-to-many relationships between two species, to discriminate between functionally equivalent and non-equivalent orthologs.
Partial RdRp sequences offer a robust method for Coronavirus subgenus classification

The recent reclassification of the Riboviria, and the introduction of multiple new taxonomic categories including both subfamilies and subgenera for coronaviruses (family Coronaviridae, subfamily Orthocoronavirinae) represents a major shift in how official classifications are used to designate specific viral lineages. While the newly defined subgenera provide much-needed standardisation for commonly cited viruses of public health importance, no method has been proposed for the assignment of subgenus based on partial sequence data, or for sequences that are divergent from the designated holotype reference genomes. Here, we describe the genetic variation of a partial region of the coronavirus RNA-dependent RNA polymerase (RdRp), which is one of the most used partial sequence loci for both detection and classification of coronaviruses in molecular epidemiology. We infer Bayesian phylogenies from more than 7000 publicly available coronavirus sequences and examine clade groupings relative to all subgenus holotype sequences. Our phylogenetic analyses are largely coherent with genome-scale analyses based on designated holotype members for each subgenus. Distance measures between sequences form discrete clusters between taxa, offering logical threshold boundaries that can attribute subgenus or indicate sequences that are likely to belong to unclassified subgenera both accurately and robustly. We thus propose that partial RdRp sequence data of coronaviruses is sufficient for the attribution of subgenus-level taxonomic classifications and we supply the R package, “MyCoV”, which provides a method for attributing subgenus and assessing the reliability of the attribution. Importance Statement The analysis of polymerase chain reaction amplicons derived from biological samples is the most common modern method for detection and classification of infecting viral agents, such as Coronaviruses. Recent updates to the official standard for taxonomic classification of Coronaviruses, however, may leave researchers unsure as to whether the viral sequences they obtain by these methods can be classified into specific viral taxa due to variations in the sequences when compared to type strains. Here, we present a plausible method for defining genetic dissimilarity cut-offs that will allow researchers to state which taxon their virus belongs to and with what level of certainty. To assist in this, we also provide the R package ‘MyCoV’ which classifies user generated sequences.
Novel mosaic mice with diverse applications

Gene-deficient mouse models are indispensable for interrogating mammalian gene functions, but the conventional models allow the study of only one or few genes per mouse line, which has been a bottleneck in functional genomics. To confront the challenge, we have combined the CRISPR-Cas and Cre-Lox systems to develop a novel type of mosaic mice termed MARC (Mosaic Animal based on gRNA and Cre) for targeting many genes per mouse but only one gene per cell. This technology employs a transgene comprising a modified U6 promoter upstream of a series of floxed gRNA genes linked together in tandem, with one gRNA expressed per cell following Cre-mediated recombination. At least 61 gRNA genes can be stably maintained in the transgene, and importantly, enables robust proof-of-principle in vivo screens, demonstrating the potential for quickly evaluating the functions of many genes in diverse tissues in a single MARC line. In theory, MARC can also be analyzed by single-cell sequencing, and should enable cost-effective derivation of conventional single-gene-KO lines via simple breeding. Our study establishes MARC as an important addition to the mouse genetics toolbox.
A Data-Independent-Acquisition-based proteomic approach towards understanding the acclimation strategy of Microchloropsis gaditana CCMP526 in hypersaline conditions

Salinity is one of the significant factors that affect growth and cellular metabolism, including photosynthesis and lipid accumulation, in microalgae and higher plants. Microchloropsis gaditana CCMP526 can acclimatize to different salinity levels by accumulating compatible solutes, carbohydrates, and lipid as an energy storage molecule. We used proteomics to understand the molecular basis for acclimation of M. gaditana to increased salinity levels (55 and 100 PSU (Practical Salinity Unit). Correspondence analysis (CA) was used for identification of salinity-responsive proteins (SRPs). The highest number of altered proteins was observed in 100 PSU. Gene Ontology (GO) enrichment analysis revealed a separate path of acclimation for cells exposed to 55 and 100 PSU. Osmolyte and lipid biosynthesis was up-regulated in high saline conditions. However, concomitantly lipid oxidation pathways were also up-regulated at high saline conditions, providing acetyl-CoA for energy metabolism through the TCA cycle. Carbon fixation and photosynthesis were tightly regulated, while chlorophyll biosynthesis was affected under high salinity conditions. Importantly, temporal proteome analysis of salinity-challenged M. gaditana revealed vital salinity-responsive proteins which could be used for strain engineering for improved salinity resistance.
Conhecimento, atitudes e controle metabólico de diabéticos cardiopatas

Objetivo: verificar a relacao do conhecimento, atitudes e controle metabolico de diabeticos cardiopatas. Metodos: estudo descritivo, exploratorio e transversal que verificou conhecimento, atitudes e controle metabolico do diabetes em 46 participantes com cardiopatia. Resultados: os participantes eram predominantemente do sexo masculino, com ensino medio incompleto, que demonstraram conhecimento insatisfatorio e atitudes desfavoraveis em relacao a doenca. Nao houve diferenca entre os participantes com e sem conhecimento em relacao as variaveis de controle metabolico e clinico do diabetes, tampouco com atitudes frente a doenca. Conclusao: o conhecimento sobre diabetes mostrou-se insatisfatorio em pacientes com cardiopatia e nao se relacionou a atitudes favoraveis e melhor controle da doenca.
Kinome Profiling of Primary Endometrial Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies SRPK1 as Candidate Therapeutic Target

Kinome profiles of endometrial tumors and normal tissues have been determined using Multiplexed Inhibitor Beads and Mass Spectrometry. Overexpression of SRPK1 in endometrial tumors was observed, which was associated with poor survival. Inhibition of SRPK1 in endometrial cancer cells revealed SRPK1 was integral for growth under serum-starved conditions. Compensatory activation of EGFR, IGF1R, and AKT promoted resistance to SRPK1 inhibitor SPHINX31. Combination therapies involving SRPK1 and EGFR or IGF1R inhibitors synergized to block growth and survival of endometrial cancer cells. Graphical Abstract Highlights SRPK1 is overexpressed in endometrial cancer and associated with poor survival. SRPK1 promotes endometrial cancer cell growth under nutrient-deprived conditions. Activation of EGFR-IGF1R-AKT signaling promotes resistance to SRPK1 inhibitors. Co-targeting SRPK1 and EGFR-IGF1R synergize blocking endometrial cancer cell growth. Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the up-regulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.