Spectral fiber-photometry derives hemoglobin-absorption changes for accurate measurement of fluorescent sensor activity Fiber-photometry is an emerging technique for recording fluorescent sensor activity in the brain. However, significant hemoglobin-absorption artifacts in fiber-photometry data may be misinterpreted as sensor activity changes. Because hemoglobin exists in nearly every location in the brain and its concentration varies over time, such artifacts could impede the accuracy of many photometry recording results. Here we present a novel use of spectral photometry technique and propose computational methods to quantify photon absorption effects by using activity-independent fluorescence signals, which can be used to derive oxy- and deoxy-hemoglobin concentration changes. Following time-locked neuronal activation in vivo, we observed that a 20% increase in CBV contributes to about a 4% decrease in green fluorescence signal and a 2% decrease in red fluorescence signal. While these hemoglobin concentration changes are often temporally delayed than the fast-responding fluorescence spikes, we found that erroneous interpretation may occur when examining pharmacology-induced sustained activity changes, and in some cases, hemoglobin-absorption could flip the GCaMP signal polarity. We provided hemoglobin-based correction methods to restore fluorescence signals across spectra and compare our results against the commonly used regression approach. We also demonstrated the utility of spectral fiber-photometry for delineating brain regional differences in hemodynamic response functions.

HighlightsO_LIHemoglobin-absorption compromises fiber-photometry recording in vivo
C_LIO_LISpectral photometry allows quantification of hemoglobin concentration changes for correction
C_LIO_LIThe proposed platform allows measuring regional differences in neurovascular transfer function
C_LI
Relationship between vestibular hair cell loss and deficits in two anti-gravity reflexes in the rat The tail-lift reflex and the air-righting reflex in rats are anti-gravity reflexes that depend on vestibular function. To begin identifying their cellular basis, this study examined the relationship between reflex loss and the graded lesions caused in the vestibular sensory epithelia by varying doses of an ototoxic compound. After ototoxic exposure, we recorded these reflexes using high speed video. The movies were used to obtain objective measures of the reflexes: the minimum angle formed by the nose, the back of the neck and the base of the tail during the tail-lift maneuver and the time to right in the air-righting test. The vestibular sensory epithelia were then collected from the rats and used to estimate the loss of type I (HCI), type II (HCII) and all hair cells (HC) in both central and peripheral parts of the crista, utricle, and saccule. As expected, tail-lift angles decreased, and air-righting times increased, while the numbers of HCs remaining in the epithelia decreased in a dose-dependent manner. The results demonstrated greater sensitivity of HCI compared to HCII to the IDPN ototoxicity, as well as a relative resiliency of the saccule compared to the crista and utricle. Comparing the functional measures with the cell counts, we observed that loss of the tail-lift reflex associates better with HCI than with HCII loss. In contrast, most HCI in the crista and utricle were lost before air-righting times increased. These data suggest that these reflexes depend on the function of non-identical populations of vestibular HCs.
Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework Current metabolic modeling tools suffer from a variety of limitations, from scalability to simplifying assumptions, that preclude their use in many applications. We recently created a modeling framework, LK-DFBA, that addresses a key gap: capturing metabolite dynamics and regulation while retaining a potentially scalable linear programming structure. Key to this frameworks success are the linear kinetics and regulatory constraints imposed on the system. However, while the linearity of these constraints reduces computational complexity, it may not accurately capture the behavior of many biochemical systems. Here, we developed three new classes of LK-DFBA constraints to better model interactions between metabolites and the reactions they regulate. We tested these new approaches on several synthetic and biological systems, and also performed the first-ever comparison of LK-DFBA predictions to experimental data. We found that no single constraint approach was optimal across all systems examined, and systems with the same topological structure but different parameters were often best modeled by different types of constraints. However, we did find that the optimal constraint approach was generally robust to local perturbations of the system, indicating that just a single wild-type dataset could allow identification of the ideal constraint for a given system. These results suggest that the availability of multiple constraint approaches will allow LK-DFBA to model a wider range of metabolic systems. Cascade screening following a polygenic risk score test: what is the risk of a relative conditional on a high score of a proband? Polygenic risk scores (PRSs) for predicting disease risk have become increasingly accurate, leading to rising popularity of PRS tests. Consider an individual whose PRS test has placed him/her at the top q-quantile of genetic risk. Recently, Reid et al. (Circ Genom Precis Med. 2021;14:e003262) have investigated whether such a finding should motivate cascade screening in the probands siblings. Specifically, using data from the UK biobank, Reid et al. computed the empirical probability of a sibling of the proband to also have a PRS at the top q-quantile. In this short note, I use the liability threshold model to compute this probability analytically (for either a sibling of the proband or for a more distant relative), showing excellent agreement with the empirical results of Reid et al., including that this probability is disease-independent. Further, I compute the probability of the relative of the proband to be affected, as a function of the quantile threshold q, the proportion of variance explained by the score, and the disease prevalence. Experimental evolution reveals post-transcriptional regulation as a novel driver of Leishmania fitness gain The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings. Dynamics of SARS-CoV-2 mutations reveals regional-specificity and similar trends of N501 and High-Frequency mutation N501Y in different levels of control measures Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths to date. Surveillance and monitoring of new mutations in the virus genome are crucial to our understanding of the adaptation of SARS-CoV-2. Moreover, how the temporal dynamics of these mutations is influenced by control measures and non-pharmaceutical interventions (NPIs) is poorly understood. Using 1 058 020 SARS-CoV-2 from sequenced COVID-19 cases from 98 countries (totaling 714 country-month combinations), we perform a normalization by COVID-19 cases to calculate the relative frequency of SARS-CoV-2 mutations and explore their dynamics over time. We found 115 mutations estimated to be present in more than 3 % of global COVID-19 cases and determined three types of mutation dynamics: High-Frequency, Medium-Frequency, and Low-Frequency. Classification of mutations based on temporal dynamics enable us to examine viral adaptation and evaluate the effects of implemented control measures in virus evolution during the pandemic. We showed that Medium-Frequency mutations are characterized by high prevalence in specific regions and/or in constant competition with other mutations in several regions. Finally, taking N501Y mutation as representative of High-Frequency mutations, we showed that level of control measure stringency negatively correlates with the effective reproduction number of SARS-CoV-2 with High-Frequency or not-High-Frequency and both follows similar trends in different levels of stringency. Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

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

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. Molecular switch between mammalian MLL complexes dictates response to Menin-MLL inhibition The chromatin adaptor Menin interacts with oncogenic fusion proteins encoded by MLL1-rearrangements (MLL1-r), and small molecules that disrupt these associations are currently in clinical trials for the treatment of leukemia. By integrating chromatin-focused and genome-wide CRISPR screens with genetic, pharmacological, and biochemical approaches in mouse and human systems, we discovered a molecular switch between the MLL1-Menin and MLL3/4-UTX chromatin modifying complexes that dictates response to Menin-MLL inhibitors. We show that MLL1-Menin safeguards leukemia survival by impeding binding of the MLL3/4-UTX complex at a subset of target gene promoters. Disrupting the interaction between Menin and MLL1 leads to UTX-dependent transcriptional activation of a tumor suppressor gene-program that is crucial for a therapeutic response in murine and human leukemia. We establish the therapeutic relevance of this mechanism by showing that CDK4/6 inhibitors allow re-activation of this tumor-suppressor program in Menin-inhibitor insensitive leukemia cells, mitigating treatment resistance. The discovery of a molecular switch between MLL1-Menin and MLL3/4-UTX complexes on chromatin sheds light on novel functions of these evolutionary conserved epigenetic mediators and is particularly relevant to understand and target molecular pathways determining response and resistance in ongoing phase 1/2 clinical trials. Heritable changes in division speed accompany the diversification of singleT cell fate Rapid clonal expansion of antigen specific T cells is a fundamental feature of adaptive immune responses. It enables the outgrowth of an individual T cell into thousands of clonal descendants that diversify into short-lived effectors and long-lived memory cells. Clonal expansion is thought to be programmed upon priming of a single naive T cell and then executed by homogenously fast divisions of all of its descendants. However, the actual speed of cell divisions in such an emerging  T cell family has never been measured with single-cell resolution. Here, we utilize continuous live-cell imaging in vitro to track the division speed and genealogical connections of all descendants derived from a single naive CD8+ T cell throughout up to ten divisions of activation-induced proliferation. This comprehensive mapping of T cell family trees identifies a short burst phase, in which division speed is homogenously fast and maintained independent of external cytokine availability or continued T cell receptor stimulation. Thereafter, however, division speed diversifies and model-based computational analysis using a novel Bayesian inference framework for tree-structured data reveals a segregation into heritably fast and slow dividing branches. This diversification of division speed is preceded already during the burst phase by variable expression of the interleukin-2 receptor alpha chain. Later it is accompanied by selective expression of memory marker CD62L in slower dividing branches. Taken together, these data demonstrate that T cell clonal expansion is structured into subsequent burst and diversification phases the latter of which coincides with specification of memory vs. effector fate.

SignificanceRapid clonal expansion of antigen-specific T cells is a fundamental feature of adaptive immune responses. Here, we utilize continuous live-cell imaging in vitro to track the division speed and genealogical connections of all descendants derived from a single naive CD8+ T cell throughout up to ten divisions of activation-induced proliferation. Bayesian inference of tree-structured data reveals that clonal expansion is divided into a homogenously fast burst phase encompassing two to three divisions and a subsequent diversification phase during which T cells segregate into quickly dividing effector T cells and more slowly cycling memory precursors. Our work highlights cell cycle speed as a major heritable property that is regulated in parallel to key lineage decisions of activated T cells. Evidence for spatiotemporal shift in demersal fisheries management priority areas in the western Mediterranean Marine Protected Areas (MPAs) are a promising management tool for the conservation and recovery of marine ecosystems, as well as fisheries management. MPAs are generally established as permanent closures but marine systems are dynamic, which has generated debate in favour of more dynamic designs. As a consequence, the identification of priority areas should assess their persistence in space and time. Here, we develop a step-by-step approach to assess the spatiotemporal dynamics of fisheries management priority areas using standard fishery-independent survey data. To do so, we fit Bayesian hierarchical spatiotemporal SDM models to different commercially important demersal species and use the resulting maps to fit different spatial prioritisation configurations. We use these results to assess the spatiotemporal dynamics of fisheries priority areas. The proposed method is illustrated through a western Mediterranean case study using fishery-independent trawl survey data on six commercially important species collected over 17 years. We identified two fisheries priority area patterns in the study area, each predominant during a different time-period of the study, asserting the importance of regularly re-assessing MPA designs. "Adopt a Microorganism" methodology enhances the discourse richness of high school students in both hybrid learning and remote education 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. Polycystin promotes renal fibrosis through EZH2 Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. EPIC: inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific gene expression measurements from single-cell RNA sequencing (scRNA-seq). We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We apply our framework to multiple scRNA-seq datasets from different platforms and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and scRNA-seq datasets and further validated using PubMed search and existing bulk case-control testing results. Lipid membranes modulate the activity of RNA through sequence-dependent interactions RNA is a ubiquitous biomolecule that can serve as both catalyst and information carrier. Understanding how RNA bioactivity is controlled is crucial for elucidating its physiological roles and potential applications in synthetic biology. Here we show that lipid membranes can act as RNA organization platforms, introducing a novel mechanism for ribo-regulation. The activity of R3C ribozyme can be modified by the presence of lipid membranes, with direct RNA-lipid interactions dependent on RNA nucleotide content, base pairing and length. In particular, the presence of guanine in short RNAs is crucial for RNA-lipid interactions, and G-quadruplex formation further promotes lipid binding. Lastly, by artificially modifying the R3C substrate sequence to enhance membrane binding we generated a lipid-sensitive ribozyme reaction with riboswitch-like behavior. These findings introduce RNA-lipid interactions as a tool for developing synthetic riboswitches and novel RNA-based lipid biosensors, and bear significant implications for RNA World scenarios for the origin of life. 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. NOMA: a high-throughput microchip for robust, sequential measurements of secretions from the same single-cells Despite recent advances in single-cell analysis technologies, lacking simple methods to keep the live single-cells traceable for longitudinal detection reliably poses a significant obstacle in single-cell secretion analysis. Here we reported the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of[&ge;] 97% of trapped single cells in dedicated spatial locations during repetitive detection procedures, verified with both adherent and suspension cells by two researchers independently. We applied it in monitoring single-cell protein secretions sequentially from the same single cells, and we found the digital protein secretion patterns dominate the protein secretion. We also demonstrated the microchip for longitudinally tracking IL-8 and the CD81+EV secretions from the same single-cells over days, which revealed the presence of "super secretors" within the cell population be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for tracking sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research.

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org.highwire.dtl.DTLVardef@aa69c7org.highwire.dtl.DTLVardef@6bc79org.highwire.dtl.DTLVardef@3fcbbforg.highwire.dtl.DTLVardef@597f4b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Disruption of the microphysiological niche alters matrix deposition and causes loss of mitochondrial Ca2+ control in skeletal muscle fibers Cells rapidly lose their physiological phenotype upon disruption of their extracellular matrix (ECM)-intracellular cytoskeleton interactions. Here, we investigated acute effects of ECM disruption on cellular and mitochondrial morphology, transcriptomic signatures, and Ca2+ handling in adult mouse skeletal muscle fibers. Adult skeletal muscle fibers were isolated from mouse toe muscle either by collagenase-induced dissociation of the ECM or by mechanical dissection that leaves the contiguous ECM intact. Experiments were generally performed four hours after cell isolation. At this time, there were striking differences in the gene expression patterns between fibers isolated with the two methods; 24h after cell isolation, enzymatically dissociated fibers had transcriptomic signatures resembling dystrophic phenotypes. Mitochondrial appearance was grossly similar in the two groups, but 3D electron microscopy revealed shorter and less branched mitochondria in enzymatically dissociated than in mechanically dissected fibers. Similar increases in free cytosolic [Ca2+] during repeated tetanic stimulation were accompanied by marked mitochondrial Ca2+ uptake only in enzymatically dissociated muscle fibers. The aberrant mitochondrial Ca2+ uptake was partially prevented by the mitochondrial Ca2+ uniporter inhibitor Ru360 and by cyclosporine A and NV556, which inhibit the mitochondrial protein Ppif (also called cyclophilin D). Importantly, inhibition of Ppif with NV556 significantly improved survival of mice with mitochondrial myopathy in which muscle mitochondria take up excessive amounts of Ca2+ even with an intact ECM. In conclusion, skeletal muscle fibers isolated by collagenase-induced dissociation of the ECM display aberrant mitochondrial Ca2+ uptake, which involves a Ppif-dependent mitochondrial Ca2+ influx resembling that observed in mitochondrial myopathies. 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. Protein reservoirs of seeds are composites of amyloid and amyloid-like structures facilitating germination The functional roles of amyloids are known across diverse species, but their natural presence in plants remains underexplored. Based on the structure and function of protein bodies found in other organisms, we hypothesize that the seed storage protein bodies (SSPB) may have amyloid structures for controlling physiological functions. Here we show that monocot and dicot SSPB exhibit a speckled-pattern of amyloids interspersed in an amyloid-like matrix, suggesting their composite nature. This is confirmed by amyloid-specific probes, amyloidogenic region scans, infrared signatures, reconstitution studies, and differential degradation during germination. The role of amyloidic composites in seed germination is proved by amyloid content, degradation inhibition and relevant germination parameters, using in-vitro SSPB, ex-vivo protoplasts and in-situ seed sections. The results open new research questions in understanding molecular details of SSPB assembly-disassembly and utilization, in addition to evolutionary roles of amyloid structure and function. Accuracy and Power Analysis of Social Networks Built From Count Data O_LIPower analysis is used to estimate the probability of correctly rejecting a null hypothesis for a given statistical model and dataset. Conventional power analyses assume complete information, but the stochastic nature of behavioural sampling can mean that true and estimated networks are poorly correlated. Power analyses do not currently take the effect of sampling into account. This could lead to inaccurate estimates of statistical power, potentially yielding misleading results.
C_LIO_LIHere we develop a method for computing network correlation: the correlation between an estimated social network and its true network, using a Gamma-Poisson model of social event rates for networks constructed from count data. We use simulations to assess how the level of network correlation affects the power of nodal regression analyses. We also develop a generic method of power analysis applicable to any statistical test, based on the concept of diminishing returns.
C_LIO_LIWe demonstrate that our network correlation estimator is both accurate and moderately robust to its assumptions being broken. We show that social differentiation, mean social event rate, and the harmonic mean of sampling times positively impacts the strength of network correlation. We also show that the required level of network correlation to achieve a given power level depends on many factors, but that 0.80 network correlation usually corresponds to around 0.80 power for nodal regression in ideal circumstances.
C_LIO_LIWe provide guidelines for using our network correlation estimator to verify the accuracy of networks built from count data, and to conduct power analysis. This can be used prior to data collection, in post hoc analyses, or even for subsetting networks in dynamic network analysis. The network correlation estimator and custom power analysis methods have been made available as an R package.
C_LI Reconstitution of minimal motility system based on Spiroplasma swimming by expressing two bacterial actins in synthetic minimal bacterium Motility is one of the most important features of life, but its evolutionary origin remains unknown. In this study, we focused on Spiroplasma, commensal, or parasitic bacteria. They swim by switching the helicity of a ribbon-like cytoskeleton that comprises six proteins, each of which evolved from a nucleosidase and bacterial actin called MreB. We expressed these proteins in a synthetic, non-motile minimal bacterium, JCVI-syn3.0B, whose reduced genome was computer-designed and chemically synthesized. The synthetic bacterium exhibited swimming motility with features characteristic of Spiroplasma swimming. Moreover, some combinations of the two proteins produced a helical cell shape and swimming, suggesting that the swimming originated from the differentiation and coupling of bacterial actins, and we also obtained a minimal system for motility of the synthetic bacterium.

One-Sentence SummaryThe minimal system comprised two bacterial actins that provided cell helicity and swimming to the synthetic minimal bacterium. Aberrant induction of p19Arf-mediated cellular senescence contributes to neurodevelopmental defects Timely induction of cellular senescence is important during embryonic development and tissue repair, while aberrant activation contributes to many age-related diseases. However, whether abnormal induction of senescence in the embryo contributes to developmental defects remains unclear. To explore this, we investigated the clinically significant model of Valproic acid- (VPA) induced developmental defects. VPA is a widely prescribed drug to treat epilepsy, bipolar disorder and migraine. If taken during pregnancy however, exposure to the developing embryo can cause birth defects, cognitive impairment and Autism-Spectrum Disorder. How VPA causes these developmental defects remains unknown. We used embryonic mice and human organoids to model key features of drug exposure, including exencephaly, microcephaly and spinal defects. In the malformed tissues, in which neurogenesis is defective, we find pronounced induction of cellular senescence in the neuroepithelial cells. Critically, through genetic and functional studies, we identified p19Arf as the instrumental mediator of senescence and microcephaly, but surprisingly, not exencephaly and spinal defects. Together, these findings uncover how misregulated senescence in neuroepithelial cells can contribute to developmental defects. The Inflammatory Role of Milk Fat Globule Epidermal Growth Factor VIII in Angiotensin II Induced Arterial Remodeling BackgroundAngiotensin II (Ang II) and milk fat globule-epidermal growth factor VIII (MFG-E8) are involved in age-associated arterial remodeling; however, the inflammatory role of MFG-E8 in Ang II associated arterial remodeling with aging remains unknown.

Methods and ResultsIn this study, 30-week-old MFG-E8 knock out (KO) and age-matched wild-type (WT) mice were infused with Ang II or saline. After infusion the with Ang II, the aortic molecular, cellular, and structural remodeling were observed in mice and compared to those infused with saline, but these effects were dependent on the expression of MFG-E8: (1) In the WT mice, Ang II infusion substantially increased intimal-medial thickness, elastic lamina degradation, collagen deposition, and the proliferation of VSMCs; in contrast, in the KO mice, these effects were significantly reduced; (2) In the WT mice, Ang II treatment significantly increased the activation and expression of MMP2, TGF-{beta}1, and its downstream signaling molecule p-SMAD2, and collagen type I production, however, in the KO mice, these molecular effects were significantly reduced; (3) In the WT mice, Ang II treatment increased inflammatory p-NF-{kappa}B p65, MCP1, TNF-, ICAM1, and VCAM1 molecular expression, while conversely, in the KO mice, no significant inflammatory changes were found; (4) Importantly, compared to untreated control mice with a wide range of age from 4-96 weeks, Ang II infused "younger" mice produced an "older" arterial inflammatory phenotype, which was alleviated by MFG-E8 deficiency.

ConclusionsMFG-E8 mediates Ang II associated arterial inflammatory remodeling. Targeting MFG-E8 is a novel molecular approach to curb adverse arterial remodeling during aging and hypertension.

CLINICAL PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABS* Both Ang II and MFG-E8 increases are involved in proinflammatory arterial remodeling mediating the molecular, cellular and tissue events in aging and hypertension.
* MFG-E8 is essential for Ang II induced and age-associated adverse arterial remodeling via the increase of proinflammation, intimal medial thickening, elastin fragmentation, collagen deposition, and VSMC proliferation.


What Are the Clinical Implications?Since MFG-E8 mediates Ang II induced proinflammation in arterial wall remodeling in aging and hypertension, targeting MFG-E8 is a potential molecular approach to curb inflammatory arterial remodeling, maintaining the health of the vascular system during aging and hypertension. Shortcuts in stochastic systems and control of biophysical processes The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time--via external interventions like time-varying concentrations of chemical species--is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. Though CD driving is limited to target trajectories that are instantaneous stationary states, we show how to generalize the approach to allow for non-stationary targets and local control--where only a subset of system states are targeted. The latter is particularly useful for biological implementations where there may be only a small number of available external control knobs, insufficient for global control. We derive simple graphical criteria for when local versus global control is possible. Finally, we illustrate the formalism with global control of a genetic regulatory switch and local control in chaperone-assisted protein folding. The derived control protocols in the chaperone system closely resemble natural control strategies seen in experimental measurements of heat shock response in yeast and E. coli. Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of pleiotropy and fitness consequences Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of specific new mutations to their effects on fitness. Here, we complete gene ontology analysis and metabolomics experiments on Arabidopsis thaliana MA lines to determine how spontaneous mutations directly affect global metabolic output in lines that have measured fitness consequences. For these analyses, we compared three lines with relative fitness consistently higher than the unmutated progenitor and three lines with lower relative fitness as measured in four different field trials. In a gene ontology analysis, we find that the high fitness lines were significantly enriched in mutations in or near genes with transcription regulator activity. We also find that although they do not have an average difference in the number of mutations, low fitness lines have significantly more metabolic subpathways disrupted than high fitness lines. Taken together, these results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and more on the pleiotropic effects of those mutations, and that organisms can explore a considerable amount of physiological space with only a few mutations.

Significance StatementAs the source of all genetic variation, new mutations are crucial for understanding how organisms adapt to their environment. However, the ways in which new mutations affect the range of metabolic reactions that occur in the cell is unknown. With a combination of gene functional analyses and measurement of the small molecules that drive cellular function and physiology, we find that mutations associated with high fitness are disproportionately found in or near proteins-coding genes that regulate the specific timing and location of gene expression and are less disruptive of cellular physiology.