title: Genetic analysis of C. elegans Haspin-like genes shows that hasp-1 plays multiple roles in the germline

abstract:
Haspin is a histone kinase that promotes error-free chromosome segregation by recruiting the Chromosomal Passenger Complex (CPC) to mitotic and meiotic chromosomes. Haspin remains less well studied than other M-phase kinases and the models explaining Haspin function have been developed primarily in mitotic cells. Here, we generate new mutations in the C. elegans Haspin homologs hasp-1 and hasp-2 and characterize their phenotypes. We show that hasp-1 is responsible for all predicted functions of Haspin and that loss of function of hasp-1 using classical and conditional alleles produces defects in germline stem cell proliferation, spermatogenesis, and confirms its role in oocyte meiosis. Genetic analysis suggests hasp-1 acts downstream of the Polo-like kinase plk-2 and shows synthetic interactions between hasp-1 and two genes expected to promote recruitment of the CPC by a parallel pathway that depends on the kinase Bub1. This work adds to the growing understanding of Haspin function by characterizing a variety of roles in an intact animal.

Summary statementWe characterize new mutations in the C. elegans homologs of the histone kinase Haspin and show roles in spermatogenesis, germline proliferation and genetic interactions during oocyte meiosis.


title: Multi-modal single-cell and whole-genome sequencing of minute, frozen specimens to propel clinical applications

abstract: Single-cell genomics are enabling technologies, but their broad clinical application remains challenging. We report an easily adaptable approach for single-cell transcriptome and T cell receptor (TCR)-sequencing, and matched whole-genome sequencing from tiny, frozen clinical specimens. We achieve similar quality and biological outputs while reducing artifactual signals compared to data from matched fresh tissue samples. Profiling sequentially collected melanoma samples from the KEYNOTE-001 trial, we resolve cellular, genomic, and clonotype dynamics that encapsulate molecular patterns of tumor evolution during anti-PD-1 therapy. To demonstrate applicability to banked biospecimens of rare diseases, we generate a large uveal melanoma liver metastasis single-cell and matched WGS atlas, which revealed niche-specific impairment of clonal T cell expansion. This study provides a foundational framework for propelling single-cell genomics to the clinical arena.

category: genomics


title: Improved Metagenomic Binning with Transformers

abstract: AO_SCPLOWBSTRACTC_SCPLOWTraditional metagenome binning methods cluster contiguous DNA sequences (contigs) based on uncontextualized features of the sequences which ignores both the semantic relationship between genes and the positional embedding of k-mers. This paper presents a novel binning method that addresses these concerns. Firstly, taken from natural language processing literature, a sequence representation model - Bidirectional Encoder Representations from Transformers (BERT) - is utilized to generate semantic and positional contig embeddings. Secondly, two workflows are presented; one which applies a hierarchical density-based clustering algorithm to find metagenomic bins and the other which incorporates contig embedding into a state-of-the-art binner. Experimental results on a publicly available metagenomic dataset show superior clustering for shorter contigs compared to traditionally used tetranucleotide frequency (TNF), reconstruction of up to 17% more high-precision genomes, and improved semantic understanding of contigs.


title: A novel Bayesian factor analysis method improves detection of genes and biological processes affected by perturbations in single-cell CRISPR screening

abstract: CRISPR screening coupled with single-cell RNA-sequencing has emerged as a powerful tool to characterize the effects of genetic perturbations on the whole transcriptome at a single-cell level. However, due to the sparsity and complex structure of data, analysis of single-cell CRISPR screening data remains challenging. In particular, standard differential expression analysis methods are often under-powered to detect genes affected by CRISPR perturbations. We developed a novel method for such data, called Guided Sparse Factor Analysis (GSFA). GSFA infers latent factors that represent co-regulated genes or gene modules, and by borrowing information from these factors, infers the effects of genetic perturbations on individual genes. We demonstrated through extensive simulation studies that GSFA detects perturbation effects with much higher power than state-of-the-art methods. Using single-cell CRISPR data from human CD8+ T cells and neural progenitor cells, we showed that GSFA identified biologically relevant gene modules and specific genes affected by CRISPR perturbations, many of which were missed by existing methods, providing new insights into the functions of genes involved in T cell activation and neurodevelopment.


title: Whole-genome resequencing reveals the population structure, genomic diversity, and demographic history of American chestnut (Castanea dentata)

abstract: American chestnut (Castanea dentata) was once the most economically and ecologically important hardwood species in the United States. In the first half of the 20th century, an exotic fungal pathogen - Cryphonectria parasitica - decimated the species, killing approximately four billion trees. Two approaches to developing blight resistant American chestnut populations show promise, but both will require introduction of adaptive genomic diversity from wild germplasm to produce diverse, locally adapted reforestation populations. Here we characterize population structure, demographic history, and genomic diversity in a range-wide sample of 384 wild American chestnuts to inform conservation and breeding with blight resistant varieties. Population structure analyses with DAPC and ADMIXTURE suggest that the chestnut range can be roughly divided into northeast, central, and southwest populations. Within-population genomic diversity estimates revealed a clinal pattern with the highest diversity in the southwest, which likely reflects bottleneck events associated with Quaternary glaciation. Finally, we identified genomic regions under positive selection within each population, which suggests that defense against fungal pathogens is a common target of selection across all populations. Taken together, these results show that American chestnut underwent a postglacial expansion from the southern portion of its range leading to three extant populations. These populations will serve as management units for breeding adaptive genetic variation into the blight-resistant tree populations for targeted reintroduction efforts.


title: Historical contingency drives compensatory evolution and rare reversal of phage resistance

abstract: Bacteria and lytic viruses (phages) engage in highly dynamic coevolutionary interactions over time, yet we have little idea of how transient selection by phages might shape the future evolutionary trajectories of their host populations. To explore this question, we generated genetically diverse phage-resistant mutants of the bacterium Pseudomonas syringae. We subjected the panel of mutants to prolonged experimental evolution in the absence of phages. Some populations re-evolved phage sensitivity, while others acquired compensatory mutations that reduced the costs of resistance without altering resistance levels. To ask whether these outcomes were driven by the initial genetic mechanisms of resistance, we next evolved independent replicates of each mutant lineage in the absence of phages. We found a strong signature of historical contingency: some mutations were highly reversible across replicate populations, while others were highly entrenched. Through whole-genome sequencing of bacteria over time, we also found that populations with resistance mutations in the same gene acquired more parallel sets of mutations than populations with resistance mutations in different genes, suggesting that compensatory adaptation is also contingent on how resistance initially evolved. Our study identifies an evolutionary ratchet in bacteria-phage coevolution, and may explain previous observations that resistance persists over time in some bacterial populations but is lost in others. We add to a growing body of work describing the key role of phages in the ecological and evolutionary dynamics of their host communities. Beyond this specific trait, our study provides new insight into the genetic architecture of historical contingency, a crucial component of interpreting and predicting evolution.

category: evolutionary biology


title: Distinctiveness and continuity in transcriptome and connectivity in the anterior-posterior axis of the paraventricular nucleus of thalamus

abstract: The paraventricular nucleus of the thalamus (PVT) projects axons to multiple areas and mediates a wide range of behaviors. Heterogeneity of functions and axonal projections in PVT have been reported, but what cell types exist in PVT and how different they are have not been addressed. We applied single-cell RNA sequencing to depict transcriptomic characteristics of mouse PVT neurons. The transcriptome of PVT neurons had a continuous distribution with the largest variance corresponding to the anterior-posterior axis. Although the single-cell transcriptome classified PVT neurons into four types, transcriptomic and histological analyses showed their continuity. Similarly, anterior and posterior subpopulations had nearly non-overlapping axon projection patterns, while another population showed intermediate patterns. In addition, they responded differently to appetite-related neuropeptides, and their chemogenetic activation showed opposing effects in food consumption. Our studies showed contrasts and continuity of PVT neurons underlying their function as a behavior-modulating hub.

category: neuroscience


title: Proprioceptive and visual feedback responses in macaques exploit goal redundancy

abstract: A common problem in motor control concerns how to generate patterns of muscle activity when there are redundant solutions to attain a behavioural goal. Optimal feedback control is a theory that has guided many behavioural studies exploring how the motor system incorporates task redundancy. This theory predicts that kinematic errors that deviate the limb should not be corrected if one can still attain the behavioural goal. Several studies in humans demonstrate that the motor system can flexibly integrate visual and proprioceptive feedback of the limb with goal redundancy within 90ms and 70ms, respectively. Here we show monkeys (Macaca mulatta) demonstrate similar abilities to exploit goal redundancy. We trained four male monkeys to reach for a goal that was either a narrow square or a wide, spatially redundant rectangle. Monkeys exhibited greater trial-by-trial variability when reaching to the wide goal consistent with exploiting goal redundancy. On random trials we jumped the visual feedback of the hand and found monkeys corrected for the jump when reaching to the narrow goal and largely ignored the jump when reaching for the wide goal. In a separate set of experiments, we applied mechanical loads to the monkeys arm and found similar corrective responses based on goal shape. Muscle activity reflecting these different corrective responses were detected for the visual and mechanical perturbations starting at [~]90 and [~]70ms, respectively. Thus, rapid motor responses in macaques can exploit goal redundancy similar to humans, creating a paradigm to study the neural basis of goal-directed motor action and motor redundancy.


title: An attempt of using public ambient temperature data in swine genetic evaluation for litter size traits at birth in Japan

abstract: To obtain the fundamental information on using ambient temperature information in developing the model for routine swine genetic evaluation in Japan, we analyzed total number born (TNB), number born alive (NBA), and number stillborn (NSB) collected at a Japanese farm, together with off-farm ambient temperature measured at a nearest Automated Meteorological Data Acquisition System station. Five repeatability animal models were exploited, considering the effects of farrowing season (model 1), farrowing month (model 2), quadratic regressions of daily maximum ambient temperature of farrowing day (model 3), season and temperature (model 4), or month and temperature (model 5). Patterns of the effects of daily maximum temperature of farrowing day estimated using model 3 was similar to those of farrowing season by model 1 and those of farrowing month by model 2. Adding the effect of daily maximum temperature of farrowing day (models 4 and 5) could explain phenotypic variability greater than only considering either of farrowing season and month (models 1 and 2). Estimated heritability was stable among the models and the rank correlation of predicted breeding values between models was >0.98 for all traits. The results indicate the possibility that using public ambient temperature can capture a large part of the phenotypic variability in litter size traits at birth caused by the seasonality in Japan and do not harm, at least, the performance of genetic evaluation. This study could support the availability of public meteorological data in flexible developing operational models for future swine genetic evaluation in Japan.

category: genetics


title: Xlnc1DCNN: An Explainable Long Non-Coding RNA Identification Tool

abstract: Long non-coding RNAs (lncRNAs) play crucial roles in many biological processes and are implicated in several diseases. With the next-generation sequencing technologies, substantial un-annotated transcripts have been discovered. Classifying unannotated transcripts using biological experiments is more time-consuming and expensive than computational approaches. Several tools for identifying long non-coding RNAs are available. These tools, however, did not explain which features in their tools contributed to the prediction results. Here, we present Xlnc1DCNN, a tool for distinguishing long non-coding RNAs (lncRNAs) from protein-coding transcripts (PCTs) using a one-dimensional convolutional neural network with prediction explanations. The evaluation results of the human test set showed that Xlnc1DCNN outperformed other state-of-the-art tools in terms of accuracy and F1-score. The explanation results revealed that lncRNA transcripts were mainly identified as sequences with no conserved regions or with a region of transmembrane helix while protein-coding transcripts were mostly classified by conserved protein domains or families. The explanation results also conveyed the probably inconsistent annotations among the public databases, lncRNA transcripts which contain protein domains or families, as well as protein-coding transcripts which are nonsense-mediated decay or processed transcripts. Xlnc1DCNN is freely available at https://github.com/cucpbioinfo/Xlnc1DCNN.

category: bioinformatics


title: Interpretable deep learning model reveals subsequences of various functions for long non-coding RNA identification


title: Locomotion-induced gain of visual responses cannot explain visuomotor mismatch responses in layer 2/3 of primary visual cortex

abstract: The aim of this work is to provide a comment on a recent paper by Muzzu and Saleem (2021). In brief, our concern is that the authors claim that visuomotor mismatch responses in mouse visual cortex can be explained by a locomotion-induced gain of visual halt responses, without directly comparing these responses to mismatch responses. Without a direct comparison, the claim that one response can explain the other appears difficult to uphold, more so because previous work finds that a uniform locomotion-induced gain cannot explain mismatch responses. To support these arguments, we analyzed a series of layer 2/3 calcium imaging datasets and show that coupling between visual flow and locomotion greatly enhances mismatch responses in an experience dependent manner compared to halts in non-coupled visual flow. This is consistent with mismatch responses representing visuomotor prediction errors. Thus, we conclude that feature selectivity cannot explain mismatch responses in mouse visual cortex.


title: The Genetics of Participation: Method and Analysis

abstract: Participation in a genetic study likely has a genetic component. Identifying such component is difficult as we cannot compare genetic information of participants with non-participants directly, the latter being unavailable. Here, we show that alleles that are more common in participants than non-participants would be further enriched in genetic segments shared by two related participants. Genome-wide analysis was performed by comparing allele frequencies in shared and not-shared genetic segments of first-degree relative pairs of the UK Biobank. A polygenic score constructed from that analysis, in non-overlapping samples, is associated with educational attainment (P = 2.1 x 10-52), body mass index (P = 1.5 x 10-19), and participation in a dietary study (P = 6.9 x 10-21). Further analysis shows that inclination to participate is a behavioural trait in its own right, and not simply a consequence of other established phenotypes. Understanding the basis of this trait is important for data analyses and the design of future surveys, genetic or otherwise.


title: Neurophysiological Measures Of Auditory Sensory Processing Are Associated With Adaptive Behavior In Children With Autism Spectrum Disorder

abstract:
BackgroundAtypical auditory cortical processing is consistently found in scalp electrophysiological and magnetoencephalographic studies of Autism Spectrum Disorder (ASD), and may provide a marker of neuropathological brain development. However, the relationship between atypical cortical processing of auditory information and adaptive behavior in ASD is not yet well understood.

MethodsWe sought to test the hypothesis that early auditory processing in ASD is related to everyday adaptive behavior through the examination of auditory event-related potentials (AEPs) in response to simple tones and Vineland Adaptive Behavior Scales in a large cohort of children with ASD (N=89), aged 6-17, and in age- and IQ-matched neurotypically (NT) developing controls (N=120).

ResultsStatistical analyses revealed significant group differences in early AEPs over temporal scalp regions. Whereas the expected rightward lateralization of the AEP to tonal stimuli occurred in both groups, lateralization of the AEP was only significantly associated with adaptive functioning, in the domains of communication and daily living, in the ASD group.

ConclusionsThese results lend support to the hypothesis that atypical processing of sensory information is related to everyday adaptive behavior in autism.


title: Investigating the effect of obesity on adipose-derived stem cells (ASCs) using Gottingen Minipigs

abstract:
Obesity is associated with low grade inflammation, which may adversely impact the biological functions of adipose tissue and consequently of adipose-derived stem cells (ASCs). Studies in humans and rodents have described that obesity alters ASC properties and functionality, compromising their therapeutic prospects. The Gottingen Minipig (GM) is a commonly used obesity model. Nevertheless, there are no studies investigating the effect of obesity on ASCs from GM, which could constitute a valuable addition to both obesity modelling and adult stem cells investigations.

In this study, we isolated subcutaneous ASCs from lean and obese GM to investigate the effect of obesity on cell behavior and differentiation capacity. During culturing, we observed an inherent difference in cell morphology between lean and obese ASCs. Upon adipogenic induction, obese-ASCs readily differentiated, developing significantly larger amounts of adipocytes than corresponding lean-ASCs, hinting at a predisposition towards adipogenic differentiation. Expression profiling of obesity-related genes in cell cultures, before and after adipogenic differentiation, revealed a tendency towards up-regulation in differentiated obese-cultures. Altogether, our results indicate that stem cells from obese donors could display different therapeutic properties. In summary, our results point towards GM as a valuable model for future ASCs investigations in healthy and obese states.

category: cell biology


title: Positional Context of Myonuclear Transcription during Injury-induced Muscle Regeneration

abstract: Fundamental aspects underlying skeletal muscle regeneration after injury are poorly understood. This investigation begins to address deficiencies in knowledge by examining the kinetics of myonuclear accretion, positioning, and global transcription during injury-induced muscle regeneration in mice. We demonstrate that myonuclear accretion plateaus within 7 d of an injury and that the majority (~70%) of myonuclei are centrally aligned in linear arrays (nuclear chains) throughout the course of regeneration. Relatively few myonuclei were found in a peripheral position (~20%) or clustered (~10%) together during regeneration. Importantly, transcriptional activity of individual myonuclei in nuclear chains was high, and greater than that of peripheral or clustered myonuclei. Transcription occurring primarily in nuclear chains elevated the collective transcriptional activity of regenerating myofibers during the later stage of regeneration. Importantly, the number of myonuclei in chains and their transcriptional activity were statistically correlated with an increase in myofiber size during regeneration. Our findings demonstrate the positional context of transcription during regeneration and highlight the importance of centralized nuclear chains in facilitating hypertrophy of regenerating myofibers after injury.


title: The global exposure of species ranges and protected areas to forest management

abstract: The majority of vertebrate species globally are dependent on forests, most of which require active protection to safeguard global biodiversity. Forests, however, are increasingly either being disturbed, planted or managed in the form of timber or food plantations. Because of a lack of spatial data, forest management has commonly been ignored in previous conservation assessments. Here we show - using a new global map of forest management - that disturbed and human managed forests cover the distributional ranges of most forest-associated species. Even more worrying, protected areas are increasingly being established in areas dominated by disturbed forests. Our results imply that species extinction risk and habitat assessments might have been overly optimistic with forest management practices being ignored. With forest restoration being in the centre of climate and conservation policies in this decade, we caution that policy makers should explicitly consider forest management.

category: ecology


title: Differential adaptive potential and vulnerability to climate-driven habitat loss in Brazilian mangroves

abstract: Geographic and environmental differences have been identified as factors influencing Brazilian mangrove trees genetic diversity. Geographically, distinct species have convergent spatial genetic structures, indicating a limited gene flow between northern and southern populations. Environmentally, genomic studies and common garden experiments have found evidence of local adaptations along the latitudinal gradient of the Brazilian coast. However, little is known about how such adaptive heterogeneity could be affected by a rapidly changing climate in the coming decades, and the combination of deforestation and climate-induced habitat loss may affect these forests and their genetic diversity. Here, we applied two genomic-environmental association methods to model the turnover of potentially adaptive alleles for two dominant mangrove trees: Avicennia germinans and A. schaueriana. We analyzed a total of 134 individuals from six populations of A. germinans and ten populations of A. schaueriana spanning the Brazilian coast from 1 {degrees}S to 28 {degrees}S. Gradient forest models identified temperature-related variables as the most important predictors for A. germinans outlier loci, whereas both temperature and precipitation were important for A. schaueriana. We modeled allele frequencies and projected them for future climatic scenarios to estimate adaptively driven vulnerability. We assessed climate-driven habitat loss through climate-only distribution models and calculated annual deforestation rates for each sampled region. Finally, to assess the vulnerability of individual populations, we combined the environmental suitability, deforestation data, and adaptive vulnerability projections. For both species, subtropical populations presented a higher vulnerability than equatorial populations to climate-driven habitat loss. We also identified deforestation rates at the sampled sites that were alarmingly higher than the global average mangrove deforestation rate. Our results provide improved estimates of the impacts of ongoing climate change and human-caused habitat loss on the distribution of mangroves and highlight the importance of site-based conservation strategies that consider individual subtropical and equatorial mangrove forests.


title: Zoogeographic patterns on very small spatial scales in rock-dwellingPlectostoma snails from Borneo(Gastropoda: Caenogastropoda: Diplommatinidae)

abstract: We mapped the fine-grained distribution patterns of Plectostoma microsnails on two small isolated limestone outcrops in Malaysian Borneo. On both hills, two species were present (P. simplex and P. concinnum on Tandu Batu; P. fraternum and P. concinnum on Tomanggong Besar), but the patterns we found were different. On Tomanggong Besar, the two species occupy different parts of the hill and meet along a narrow hybrid zone that is characterised by a significantly higher rate of predation by Atopos slugs. On Tandu Batu, the two species broadly overlap and do not form hybrids. The predation rate here is the same in both species, regardless of whether they occur in monospecific localities or in mixed localities. Our results show that even small limestone outcrops of a few hundred m in diameter cannot be considered to be uniformly populated by limestone dwelling snails, and a detailed analysis of intra-hill patterns may reveal information on species differences and maintenance.


title: Divergence amid recurring gene flow: complex demographic processes during speciation are the growing expectation for forest trees

abstract: Long-lived species of trees, especially conifers, often display weak patterns of reproductive isolation, but clear patterns of local adaptation and phenotypic divergence. Discovering the evolutionary history of these patterns is paramount to a generalized understanding of speciation for long-lived plants. We focus on two closely related yet phenotypically divergent pine species, Pinus pungens and P. rigida, that co-exist along high elevation ridgelines of the southern Appalachian Mountains. Based on genome-wide RADseq data, patterns of population structure for each species were uncorrelated to geography and the environment. Signals of admixture, however, were present range- wide. When combined with information from contemporary and historical species distribution models, these patterns are consistent with a complex evolutionary history of speciation. This was confirmed using inferences based on the multidimensional site- frequency spectrum, where demographic modeling inferred recurring gene flow since divergence (9.3 - 15.4 million years ago) and population size reductions that align in timing with the last interglacial period ([~]120 - 140 thousand years ago). This suggests that phenotypic and genomic divergence, including the evolution of divergent phenological schedules leading to partial reproductive isolation, as previously documented for these two species, can happen rapidly, even between long-lived species of pines.


title: DNA-functionalized Gold Nanorods for Targeted Triple-modal Optical Imaging and Photothermal Therapy of Triple-negative Breast Cancer

abstract: Targeted imaging and therapy for triple-negative breast cancer (TNBC) in the perioperative period are believed to be imperative for better disease management and improved life expectancy. Still, they are not yet available in clinical settings, and only a few nanoparticle-based theranostic agents potentially offer these capabilities. Herein, we develop an innovative class of biocompatible triple-modality nanoprobes (TMNPs) that offer optical imaging using optoacoustic, fluorescence, and surface-enhanced Raman scattering (SERS), as well as photothermal therapy (PTT) with near-infrared (NIR) light. The TMNPs are fabricated by immobilizing positively charged NIR fluorophores on negatively charged DNA-coated gold nanorods (AuNR), then silica encapsulation. The DNA-based design allows the screening of commercially available positively charged NIR fluorophores for the optimum fluorescence and SERS signals. After the design optimization, we functionalize TMNPs with folate groups to target folate receptor1 (FOLR1)-overexpressing TNBC in vitro and in vivo. Our results reveal that TMNPs preferentially accumulate in the FOLR1 positive tumors in TNBC patient-derived xenograft mouse models and show excellent imaging capabilities with all three imaging modalities. Selective exposure of the tumor with NIR laser further shows efficient thermal tissue ablation without causing systemic toxicity. Collectively, TMNP holds great promise for real-time multiplexed imaging of cancer biomarkers and therapeutic capability.

category: bioengineering


title: Characterization of the Interaction of Nanobubble Ultrasound Contrast Agents with Human Blood Components

abstract: Nanoscale ultrasound contrast agents, or nanobubbles, are being explored in preclinical applications ranging from vascular and cardiac imaging to targeted drug delivery in cancer. These sub-micron particles are approximately 10x smaller than clinically available microbubbles. This allows them to effectively traverse compromised physiological barriers and circulate for extended periods of time. While various aspects of nanobubble behavior have been previously examined, their behavior in human whole blood has not yet been explored. Accordingly, herein we examined, for the first time, the short and long-term effects of blood components on nanobubble acoustic response. We observed differences in the kinetics of backscatter from nanobubble suspensions in whole blood compared to bubbles in phosphate buffered saline (PBS), plasma, or red blood cell solutions (RBCs). Specifically, after introducing nanobubbles to fresh human whole blood, signal enhancement gradually increased by 22.8 {+/-} 13.1% throughout our experiment, with peak intensity reached within 145 seconds. In contrast, nanobubbles in PBS had a stable signal with negligible change in intensity (-1.7 {+/-} 3.2%) over 8 minutes. Under the same conditions, microbubbles made with the same lipid formulation showed a -56.8 {+/-} 6.1% decrease in enhancement. Subsequent confocal, fluorescent, and scanning electron microscopy analysis revealed attachment of the nanobubbles to the surface of RBCs, suggesting that direct interactions, or hitchhiking, of nanobubbles on RBCs in the presence of plasma may be a possible mechanism for the observed effects. This phenomenon could be key to extending nanobubble circulation time and has broad implications in drug delivery, where RBC interaction with nanoparticles could be exploited to improve delivery efficiency.


title: Navigation of Ultrasound-controlled Swarmbots under Physiological Flow Conditions

abstract:
Navigation of microrobots in living vasculatures is essential in realizing targeted drug delivery and advancing non-invasive surgeries. We developed acoustically-controlled "swarmbots" based on the self-assembly of clinically-approved microbubbles. Ultrasound is noninvasive, penetrates deeply into the human body, and is well-developed in clinical settings. Our propulsion strategy relies in two forces: the primary radiation force and secondary Bjerknes force. Upon ultrasound activation, the microbubbles self-assemble into microswarms, which migrate towards and anchor at the containing vessels wall. A second transducer, which produces an acoustic field parallel to the channel, propels the swarms along the wall. We demonstrated cross- and upstream navigation of the swarmbots at 3.27 mm/s and 0.53 mm/s, respectively, against physiologically-relevant flow rates of 4.2 - 16.7 cm/s. Additionally, we showed swarm controlled manipulation within mice blood and under pulsatile flow conditions of 100 beats per minute. This capability represents a much-needed pathway for advancing preclinical research.

TeaserNavigation of ultrasound-guided microrobots inside artificial blood vessels overcoming physiological conditions, including high flow rates, pulsatile flow regimes, and high cell concentrations of blood.


title: Molecular Characterization in 3D Structure of MicroRNA Expressed in Leprosy

abstract:
IntroductionHansens disease, or leprosy, is a major public health problem in developing countries, caused by Mycobacterium leprae, and affecting the skin and peripheral nerves. However, M. leprae can also affect bone tissue, mucous membranes, liver, eyes, and testicles, producing a variety of clinical phenotypes. MicroRNAs (miRNAs) have been expressed in the various clinical forms of leprosy and could potentially be used for its diagnosis.

ObjectiveIn silico design of the molecular structure of miRNAs expressed in leprosy.

MethodWe performed a nucleotide sequence search of 17 miRNAs expressed in leprosy, designing in silico the molecular structure of the following miRNAs: miRNA-26a, miRNA-27a, miRNA-27b, miRNA-29c, miRNA-34c, miRNA-92a-1, miRNA-99a-2, miRNA-101-1, miRNA-101-2, miRNA-125b-1, miRNA-196b, miRNA-425-5p, miRNA-452, miRNA-455, miRNA-502, miRNA-539, and miRNA-660. We extracted the nucleotides were from the GenBank of National Center for Biotechnology Information genetic sequence database. We aligned the extracted sequences with the RNA Folding Form, and the three-dimensional molecular structure design was performed with the RNAComposer.

ResultsWe demonstrate the nucleotide sequences, and molecular structure projection of miRNAs expressed in leprosy, and produces a tutorial on the molecular model of the 17 miRNAs expressed in leprosy through in silico projection processing of their molecular structures.

ConclusionWe demonstrate in silico design of selected molecular structures of 17 miRNAs expressed in leprosy through computational biology.


title: A Self-attention Graph Convolutional Network for Precision Multi-tumour Early Diagnostics with DNA Methylation Data

abstract: DNA methylation data-based precision tumour early diagnostics is emerging as the state of the art for molecular tumour recognition, which could capture the signals of cancer occurrence 3~5 years in advance and clinically more homogenous groups. However, the sensitive of early detection for many tumors is about 30%, which needs to be greatly improved. Nevertheless, on the basis of the whole genome bisulfite sequencing methylation data, a comprehensive characterisation of the entire molecular genetic landscape of the tumor as well as the subtle differences between different tumours could be identified. With the accumulation of methylation data, high performance deep learning models that considering and modeling more unbiased information need to be developed. According to the above analysis, we designed a pipeline to investigate genome-wide DNA methylation patterns for precision multi-tumour early diagnostics. We proposed a graph convolutional network considering the attention mechanism to dissect DNA methylation heterogeneity of different cancer types. The attention mechanism in the graph convolutional network architecture could detect the cancer signals from genome-wide methylated molecular interactions, improving the robustness and sensitivity of multi-tumor classification. Experimental results demonstrates the feasibility of precision multi-tumour early diagnostics with the DNA methylation data. The workflow presented here is very useful for tumor classification, which highly relevant for the future blood diagnosis and treatment of the tumour.


title: DILIc: An AI-based classifier to search for Drug-Induced Liver Injury literature

abstract: Drug-Induced Liver Injury (DILI) is a class of Adverse Drug Reactions (ADR) which causes problems in both clinical and research settings. It is the most frequent cause of acute liver failure in the majority of western countries and is a major cause of attrition of novel drug candidates. Manual trawling of literature for is the main route of deriving information on DILI from research studies. This makes it an inefficient process prone to human error. Therefore, an automatized AI model capable of retrieving DILI-related papers from the huge ocean of literature could be invaluable for the drug discovery community. In this project, we built an artificial intelligence (AI) model combining the power of Natural Language Processing (NLP) and Machine Learning (ML) to address this problem. This model uses NLP to filter out meaningless text (e.g. stopwords) and uses customized functions to extract relevant keywords as singleton, pair, triplet and so on. These keywords are processed by apriori pattern mining algorithm to extract relevant patterns which are used to estimate initial weightings for a ML classifier. Along with pattern importance and frequency, an FDA-approved drug list mentioning DILI adds extra confidence in classification. The combined power of these methods build a DILI classifier (DILIC) with 94.91% cross-validation and 94.14% external validation accuracy. To make DILIC as accessible as possible, including to researchers without coding experience, an R Shiny App capable of classifing single or multiple entries for DILI is developed to enhance ease of user experience and made available at https://researchmind.co.uk/diliclassifier/).


title: Optimisation-based modelling for drug discovery in malaria

abstract: The discovery of new antimalarial medicines with novel mechanisms of action is important, given the ability of parasites to develop resistance to current treatments. Through the Open Source Malaria project that aims to discover new medications for malaria, several series of compounds have been obtained and tested. Analysis of the effective fragments in these compounds is important in order to derive means of optimal drug design and improve the relevant pharmaceutical application. We have previously reported a novel optimisation-based method for quantitative structure-activity relationship modelling, modSAR, that provides explainable modelling of ligand activity through a mathematical programming formulation. Briefly, modSAR clusters small molecules according to chemical similarity, determines the optimal split of each cluster into appropriate regions, and derives piecewise linear regression equations to predict the inhibitory effect of small molecules. Here, we report application of modSAR in the analysis of OSM anti-malarial compounds and illustrate how rules generated by the model can provide interpretable results for the contribution of individual ECFP fingerprints in predicting ligand activity, and contribute to the search for effective drug treatments.


title: Comparative single-cell transcriptional atlases of Babesia species reveal conserved and species-specific expression profiles

abstract: Babesia is a genus of Apicomplexan parasites that infect red blood cells in vertebrate hosts. Pathology occurs during rapid replication cycles in the asexual blood-stage of infection. Current knowledge of Babesia replication cycle progression and regulation is limited and relies mostly on comparative studies with related parasites. Due to limitations in synchronizing Babesia parasites, fine-scale time-course transcriptomic resources are not readily available. Single-cell transcriptomics provides a powerful unbiased alternative for profiling asynchronous cell populations. Here, we applied single-cell RNA sequencing to three Babesia species (B. divergens, B. bovis, and B. bigemina). We used analytical approaches and algorithms to map the replication cycle and construct pseudo-synchronized time-course gene expression profiles. We identify clusters of co-expressed genes showing just-in-time expression profiles, with gradually cascading peaks throughout asexual development. Moreover, clustering analysis of reconstructed gene curves reveals coordinated timing of peak expression in epigenetic markers and transcription factors. Using a regularized Gaussian Graphical Model, we reconstructed co-expression networks and identified conserved and species-specific nodes. Motif analysis of a co-expression interactome of AP2 transcription factors identified specific motifs previously reported to play a role in DNA replication in Plasmodium species. Finally, we present an interactive web-application to visualize and interactively explore the datasets.


title: Examining clustered somatic mutations with SigProfilerClusters

abstract:
SummaryClustered mutations are found in the human germline as well as in the genomes of cancer and normal somatic cells. Clustered events can be imprinted by a multitude of mutational processes, and they have been implicated in both cancer evolution and development disorders. Existing tools for identifying clustered mutations have been optimized for a particular subtype of clustered event and, in most cases, relied on a predefined inter-mutational distance (IMD) cutoff combined with a piecewise linear regression analysis. Here we present SigProfilerClusters, an automated tool for detecting all types of clustered mutations by calculating a sample-dependent IMD threshold using a simulated background model that takes into account extended sequence context, transcriptional strand asymmetries, and regional mutation densities. SigProfilerClusters disentangles all types of clustered events from non-clustered mutations and annotates each clustered event into an established subclass, including the widely used classes of doublet-base substitutions, multi-base substitutions, omikli, and kataegis. SigProfilerClusters outputs non-clustered mutations and clustered events using standard data formats as well as provides multiple visualizations for exploring the distributions and patterns of clustered mutations across the genome.

AvailabilitySigProfilerClusters is freely available at https://github.com/AlexandrovLab/SigProfilerClusters with support across most operating systems and extensive documentation at https://osf.io/qpmzw/wiki/home/.

Contactebergstr@eng.ucsd.edu or L2alexandrov@health.ucsd.edu


title: WlzWarp: An Open-Source Tool for Complex Alignment of Spatial Data

abstract:
BackgroundThe spatio-temporal organisation of many biological processes such as gene-expression and neuronal activity is critical to understanding the overall biological behaviour, phenotype and disease. This is especially true during embryonic development. During development spatial patterns of gene expression are key to segmentation, tissue differentiation and organ development. In situ techniques can reveal the activity of genes and the presence of proteins to a very high sub-cellular resolution but typically at high resolution only a few probes can be used on any sample therefore to compare many such patterns requires mapping of image-based data to a standard spatial framework. Once mapped those data can be collated, queried and analysed in purely spatial terms to reveal unknown combinatorial gene-activity that could not be discovered any other way. Mapping spatial data to image domains with systematic variation in shape and pose, such as embryos or elongated organs, presents special problems. Automated techniques available for more constrained systems can not deliver the mapping fidelity required to analyse these data therefore we have developed a manual editing tool, WlzWarp, for mapping 3D image data using the constrained distance transform (CDT) which uniquely can deliver the complex transforms required.

ResultsWe have implemented a fully open-source tool (available on GitHub), WlzWarp to provide interactive complex spatial mapping of 3D image data. We have applied WlzWarp to map a set of gene-expression patterns in the developing mouse embryo that could not be mapped by any other technique. The transform procedure was tested by using multiple images of the same gene from independent samples and thereby testing the full end-to-end mapping process. WlzWarp is implemented in C++ using open-source packages Qt, Coin and SIMVoleon for cross-architecture compatibility. It has been developed under Linux but also tested on Mac OSX and MS Windows.

ConclusionsWlzWarp is a freely available software tool for non-linear registration and alignment of complex 2D & 3D spatial patterns from one image to another or to an atlas model. It has been tested in the context of embryo data but can be used for any 3D or 2D image registration problem.


title: Scalable sequence database search using Partitioned Aggregated Bloom Comb-Trees

abstract: A public database such as the SRA (Sequence Read Archive) has reached 30 peta-bases of raw sequences and doubles its nucleotide content every two years. While BLAST-like methods can routinely search a sequence in a single genome or a small collection of genomes, making accessible such immense resources is out of reach for alignment-based strategies. In the last years, an abundant literature tackled the fundamental task of locating a sequence in an extensive dataset collection by converting the query and datasets to k-mers sets and computing their intersections. Among those methods, approximate membership query data structures conjugate the ability to query small signatures or variants while being scalable to collections of thousands of sequencing experiments. However, at present, more than 10,000 eukaryotic samples are not analyzable in reasonable time and space frames. Here we present PAC, a novel approximate membership query data structure for querying collections of sequence datasets. PAC presents several advantages over the state-of-the-art, enabling users to scale to the next order of magnitude. PAC index construction works in a streaming fashion without any disk footprint besides the index itself. It shows a 3 to 6 fold improvement in construction time compared to other compressed methods for comparable index size. Using inverted indexes and a novel data structure dubbed aggregative Bloom filters, a PAC query can need single random access and be performed in constant time in favorable instances. Thanks to efficient partitioning techniques, index construction and queries can be performed in parallel with a low memory footprint. Using limited computation resources and in five days, we built a PAC index that included more than 30,000 human RNA-seq samples (corresponding to more than 40 billion distinct k-mers) to assess PACs scalability. We also showed that PACs ability to query 500,000 transcript sequences in less than an hour. The only bottleneck being the index size, PAC should scale on hundred of thousand datasets on a regular cluster. PAC is open-source software available at https://github.com/Malfoy/PAC.


title: Control of protein-based pattern formation via guiding cues

abstract: Proteins control many vital functions in living cells, such as cell growth and cell division. Reliable coordination of these functions requires the spatial and temporal organizaton of proteins inside cells, which encodes information about the cells geometry and the cell-cycle stage. Such protein patterns arise from protein transport and reaction kinetics, and they can be controlled by various guiding cues within the cell. Here, we review how protein patterns are guided by cell size and shape, by other protein patterns that act as templates, and by the mechanical properties of the cell. The basic mechanisms of guided pattern formation are elucidated with reference to recent observations in various biological model organisms. We posit that understanding the controlled formation of protein patterns in cells will be an essential part of understanding information processing in living systems.

category: biophysics


title: The OncoLoop network-based precision oncology framework

abstract:
At present, prioritizing cancer treatments at the individual patient level remains challenging, and performing co-clinical studies using patient-derived models in real-time is often not feasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict and validate drug sensitivity in human tumors and their pre-existing high-fidelity (cognate) model(s) by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer (PCa) using a series of genetically-engineered mouse models (GEMMs) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of published cohorts using Master Regulator (MR) conservation analysis revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one cognate patient-derived xenograft (PDX). OncoLoop is a highly generalizable framework that can be extended to other cancers and potentially other diseases.

Significance StatementOncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround co-clinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available.

category: cancer biology


title: OncoLoop: A network-based precision cancer medicine framework


title: Semaphorin 3G exacerbates joint inflammation through the accumulation and proliferation of macrophages in the synovium

abstract:
ObjectiveMethotrexate (MTX) is an anchor drug for rheumatoid arthritis (RA) treatment; however, the exact mechanisms by which MTX improves RA activity are still debatable. This study aimed to understand the roles of molecules whose expression is affected by MTX in RA patients and find novel therapeutic targets.

MethodsCD4+ T cells from 28 treatment naive RA patients before and 3 months after the initiation of MTX treatment were subjected to DNA microarray analyses. The expression of Semaphorin 3G (Sema3G), as one of the differentially-expressed genes, and its receptor, Neuropilin-2 (Nrp2), was evaluated in RA synovium and collagen-induced arthritis (CIA) synovium. CIA and collagen antibody-induced arthritis (CAIA) were induced in Sema3G-deficient (Sema3G-/-) mice and control mice, and the clinical score, histological score, and serum cytokines were assessed. The migration and proliferation of Sema3G-stimulated bone marrow-derived macrophages (BMMs) were analyzed in vitro. The effect of local Sema3G administration during CAIA on the clinical score and the quantity of infiltrating macrophages was evaluated.

ResultsThe expression of Sema3G in CD4+ T cells was downregulated by MTX treatment in RA patients. Sema3G was expressed in RA but not osteoarthritis synovium, and its receptor Nrp2 was mainly expressed on activated macrophages. Sema3G deficiency ameliorated CIA and CAIA. Sema3G stimulation enhanced the migration and proliferation of BMMs. The local administration of Sema3G deteriorated CAIA and increased infiltrating macrophages.

ConclusionsUpregulation of Sema3G in RA synovium is a novel mechanism to deteriorate joint inflammation through the accumulation of macrophages.

Key messagesSemaphorin 3G is expressed in the inflamed synovium in human and mice.

The receptor of Semaphorin 3G is mainly expressed on M1 macrophages.

Semaphorin 3G deteriorates inflammatory arthritis through macrophage proliferation and migration.

category: pathology


title: Residual force enhancement within the human quadriceps is greatest during submaximal stretch-hold contractions at a very long muscle length

abstract: Little is known about how muscle length affects residual force enhancement (rFE) in humans. We therefore investigated rFE at short, long, and very long muscle lengths within the human quadriceps and patellar tendon (PT) using conventional dynamometry with motion capture (rFETQ) and a new, non-invasive shear-wave tensiometry technique (rFEWS). Eleven healthy male participants performed submaximal (50% max.) EMG-matched fixed-end reference and stretch-hold contractions across these muscle lengths while muscle fascicle length changes of the vastus lateralis (VL) were captured using B-mode ultrasound. We found significant rFETQ at long (7{+/-}5%) and very long (12{+/-}8%) but not short (2{+/-}5%) muscle lengths, whereas rFEWS was only significant at the very long (38{+/-}27%), but not short (8{+/-}12%) or long (6{+/-}10%) muscle lengths. We also found significant relationships between VL fascicle length and rFETQ (r=0.63, p=.001) and rFEWS (r=0.52, p=.017), but relationships were not significant between VL fascicle stretch amplitude and rFETQ (r=0.33, p=.126) or rFEWS (r=0.29, p=.201). PT shear-wave speed-angle relationships did not agree with estimated quadriceps muscle force-angle relationships, which indicates that estimating PT loads from shear-wave tensiometry might be inaccurate. We conclude that increasing muscle length rather than stretch amplitude contributes more to rFE during submaximal voluntary contractions of the human quadriceps.

category: physiology


title: In vivo calcium imaging identifies functionally and molecularly distinct subsets of tongue-innervating mechanosensory neurons

abstract: Mechanosensory neurons in the mouth provide essential information to guide feeding and speech. How classes of oral mechanoreceptors contribute to oral behaviors is not well understood; in particular, the functional properties of lingual mechanoreceptors remain elusive. Previous work identified putative mechanosensory endings in the tongue with novel morphologies; how these fit into current knowledge of mechanosensory neuron classification is not known. To identify functional classes of lingual mechanosensory neurons, we used in vivo calcium imaging of trigeminal ganglia. We first investigated calcium responses of tongue-innervating trigeminal neurons to thermal and mechanical stimulation (e.g., pressure, fluid flow, temperature changes). We found that around 17% of neurons responded to pressure, and that these pressure responders were significantly larger than neurons that only responded to temperature changes. To further investigate the cadre of functionally distinct mechanosensory neurons, we tested responses to brushing and sustained pressures and found that brush-sensitive neurons comprise the majority of tongue-innervating mechanosensory trigeminal neurons. Qualitatively, mechanosensory neurons responded to pressure with distinct kinetics, suggesting the presence of multiple classes of mechanoreceptors. To determine the number of classes, we developed an unbiased multi-layer hierarchical clustering approach to classify calcium response characteristics to pressure stimulation. This approach revealed that mechanosensory neurons displayed five distinct stimulus-response profiles to pressure. Classes include neuronal populations with sustained, transient, high-threshold, and negative responses to force as well as neurons that responded only to brushing. Analysis of cluster representation in transgenic animals with only subsets of labeled neurons reveals molecular markers of clusters and end organ structures. These studies are amongst the first to determine the functional properties of low-threshold mechanosensory neurons innervating the mouse tongue.


title: Ventral motor thalamic input to prelimbic cortex, but not to striatum, mediates cost-benefit decision-making in rats

abstract: Both prelimbic corticostriatal neurons and striatal fast-spiking interneurons contribute to decisions that require a trade-off between cost and benefit. We investigated whether ventral motor thalamic input to prelimbic cortex or striatum contributes to cost-benefit decision-making. Optogenetic inhibition of ventral motor thalamic axon terminals in prelimbic cortex biased rats towards a high cost-high benefit option and, in anesthetized rats, decreased neuronal activity in deep layers of prelimbic cortex. Stimulation of ventral motor thalamic nuclei induced a neuronal response in deep layers of prelimbic cortex and simultaneous optogenetic inhibition of layer 1 inhibitory interneurons similarly decreased neuronal activity. Chemogenetic inhibition of striatal-projecting ventral motor thalamic neurons did not affect cost-benefit decision-making. Our results indicate that ventral motor thalamic input to prelimbic cortex, but not striatum, mediates cost-benefit decision-making, probably by regulating prelimbic corticostriatal neuron activity directly as well as indirectly through a network of cortical inhibitory interneurons.


title: Decoding Dynamically Shifting States of Parkinson's Disease: Tremor, Bradykinesia, and Effective Motor Control

abstract:
Parkinsons Disease (PD) is characterized by distinct motor phenomena that are expressed asynchronously. Understanding the neurophysiological correlates of these different motor states could facilitate monitoring of disease progression and allow improved assessments of therapeutic efficacy, as well as enable optimal closed-loop neuromodulation. We examined neural activity in the basal ganglia and cortex of subjects with PD during a quantitative motor task to decode tremor and bradykinesia -- two cardinal motor signs of this disease -- and relatively asymptomatic periods of behavior. Analysis of subcortical and cortical signals revealed that tremor and bradykinesia had distinct, nearly opposite neural signatures, while effective motor control displayed unique, differentiating features. The neurophysiological signatures of these motor states depended on the type of signal recorded as well as the location; cortical decoding accuracy generally outperformed subcortical decoding, while tremor and bradykinesia were better decoded from different portions of the subthalamic nucleus (STN). These results provide a roadmap to leverage real-time neurophysiology to understand and treat PD.

One Sentence SummaryMotor signs of Parkinsons disease such as tremor and bradykinesia can be independently decoded from subthalamic and cortical recordings.


title: In-vivo estimation of axonal morphology from MRI and EEG data

abstract:
PurposeWe present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in-vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity.

TheoryThe proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on 1) the distribution of axonal radius - P(r)- and 2) the g-ratio of the individual axons that compose this tract - g(r). P(r)is assumed to follow a Gamma distribution with mode and scale parameters, M and{theta} , and g(r) is described by a power-law with parameters  and {beta}.

MethodsMRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract.

ResultsThe estimated interhemispheric transfer time was 11.72{+/-}2.87 ms, leading to an average conduction velocity across subjects of 13.22{+/-}1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated{theta} - the width of the right tail of the axonal radius distribution and {beta} - the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter{theta} was 0.40{+/-}0.07 {micro}m and the parameter {beta} was 0.67{+/-}0.02 {micro}m-.

ConclusionsThe estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in-vivo histological studies of the human brain.


title: Ghrelin receptor signaling contributes to fasting-induced suppression of conditioned avoidance behavior and neural circuit activation in male rats

abstract:
Interoceptive feedback to the brain regarding the bodys physiological state plays an important role in guiding motivated behaviors. For example, a state of negative energy balance tends to increase exploratory/food-seeking behaviors while reducing avoidance behaviors. We recently reported that overnight food deprivation reduces conditioned passive avoidance behavior in male (but not female) rats. Since fasting increases circulating levels of ghrelin, we hypothesized that ghrelin signaling contributes to the observed behavioral effect of fasting. To test this, ad libitum-fed male rats were trained in a passive avoidance procedure using mild footshock. Later, following overnight food deprivation, the same rats were pretreated with ghrelin receptor antagonist (GRA) or saline vehicle 30 min before avoidance testing. GRA restored passive avoidance in fasted rats as measured both by latency to enter and time spent in the shock-paired context. In addition, compared to vehicle-injected fasted rats, fasted rats that received GRA before re-exposure to the shock-paired context displayed more activation of prolactin-releasing peptide (PrRP)-positive noradrenergic neurons in the caudal nucleus of the solitary tract, accompanied by more activation of downstream neurons in the bed nucleus of the stria terminalis and paraventricular nucleus of the hypothalamus. These results support the view that ghrelin signaling contributes to the inhibitory effect of fasting on learned passive avoidance behavior, perhaps by suppressing recruitment of PrRP-positive noradrenergic neurons and their downstream hypothalamic and limbic forebrain targets.

Significance StatementMotivated approach and avoidance behaviors are modulated by interoceptive feedback regarding physiological state. In rats, a state of energy deficit reduces avoidance of an aversively conditioned context. Here we demonstrate a role for ghrelin signaling in this effect, such that ghrelin reduces activation of noradrenergic projections from hindbrain to hypothalamus and limbic forebrain. These novel results point to a potential mechanism by which metabolic state influences learned avoidance. Improved understanding of how interoceptive feedback signals are integrated with emotional memories that drive motivated behavior should enhance development of improved therapies for anxiety and stress-related disorders.


title: Learning vs. minding: How subjective costs can mask motor learning

abstract:
When learning new movements older adults tend to make larger kinematic errors than younger adults, interpreted as an age-related decline in motor-learning ability. However, this conclusion assumes that both older and younger adults use the same error-canceling strategy. Alternatively, it could be that older adults higher errors can be explained by a difference in strategy, rather than a reduction in learning ability. Consider that error-cancelling strategies can incur higher effort costs. Older adults may be choosing to sacrifice error reduction in favor of a lower effort movement. We test this hypothesis using trajectories where subjects reached to targets in a force field. Utilizing the framework of optimal control theory, we infer subjective costs (i.e., strategies) and internal model accuracy (i.e., proportion of the novel dynamics learned) by fitting a model to each populations trajectory data. Our results demonstrate that the trajectories are not uniquely specified by a precise amount of learning, but rather through a combination of the amount learned and strategic differences represented by relative cost weights. Based on the model fits, younger adults learn between 60-85% of the novel dynamics, and older adults learn between 55-80%. Each model fit produces trajectories which match the experimentally observed data, where a lower proportion learned in the model is compensated for by increasing costs on kinematic errors relative to effort. This finding supports our hypothesis that older and younger adults could be learning to the same extent, but older adults have a higher relative cost on effort compared to younger adults. These results call into question the proposition that older adults learn less than younger adults and suggest that the metrics commonly used to probe motor learning paint an incomplete picture. Importantly, to accurately quantify the learning process the subjective costs of movements should be considered.

Author SummaryHere we show that how a person values effort versus error in their movements has an impact on their overall strategy for performing those movements and adapting to a novel environment. When error alone is considered as a measure of learning--a widely held assumption in the field of motor control--it appears that certain populations such as older adults are significantly worse at learning new motor tasks. However, using a novel framework, we are able to parse out differences in how much a population has learned, as well as how they subjectively value factors such as effort and error. In the case of older adults, we show that they could be learning as much as younger adults but exhibit larger errors because they care more about expending extra effort to reduce them.


title: Functional MRI reveals memories of mother in newborn chicks

abstract: Filial imprinting has been used as a powerful ethological paradigm to investigate the neurobiology of early learning that affects lifelong behaviours. When a visually naive chick is exposed to one of a wide range of conspicuous objects, it may learn its characteristics and subsequently recognises and selectively approaches this stimulus (usually the mother hen and siblings). While the initial phases of memory acquisition have been unravelled, the long-term storage and retrieval components of imprinting memories are still unknown. Here, we used functional MRI in awake newly hatched chicks to identify the long-term storage of imprinting memories in a wide network comprising the hippocampal formation, the medial striatum, the arcopallium, and the prefrontal-like nidopallium caudolaterale. These results provide the first example of non-invasive imaging of the brain in a newborn vertebrate.


title: Intercontinental movement of H5 2.3.4.4 Highly Pathogenic Avian Influenza A(H5N1) to the United States, 2021

abstract: Eurasian-origin highly pathogenic avian influenza A(H5N1) belonging to the Gs/GD lineage, clade 2.3.4.4b, was detected in two Atlantic states in wild waterfowl in the United States in January 2022. Bird banding data show widespread movement of waterfowl both within the Atlantic Flyway and between neighboring flyways and northern breeding grounds.

category: microbiology


title: Conserved basal lamina proteins, laminin and nidogen, are repurposed to organize mechanosensory complexes responsible for touch sensation.

abstract: The sense of touch is conferred by the conjoint function of somatosensory neurons and skin cells. These cells meet across a gap filled by a basal lamina, an ancient structure found in all metazoans. Using Caenorhabditis elegans nematodes, we show that mechanosensory complexes essential for touch sensation reside at this interface and contain laminin, nidogen, and the MEC-4 mechano-electrical transduction channel proteins. These proteins fail to coalesce into discrete, stable structures in dissociated neurons and in touch-insensitive mec-1, mec-9 and mec-5 secreted ECM protein mutants. MEC-4, but not laminin or nidogen, is destabilized in animals where somatosensory neurons secrete MEC-1 carrying missense mutations in the C-terminal Kunitz domain. Thus, neuron-epithelial cell interfaces are instrumental in mechanosensory complex assembly and function. Drawing on computational modeling, we propose that these complexes concentrate mechanical stress into discrete foci and they enhance touch sensitivity. Consistent with this idea, loss of nidogen reduces the density of mechanoreceptor complexes, the amplitude of the touch-evoked currents they carry, and touch sensitivity in parallel. These findings imply that somatosensory neurons secrete proteins that actively repurpose the basal lamina to generate special-purpose mechanosensory complexes responsible for vibrotactile sensing.


title: Density dependence generates spatial overdispersion in adult tropical trees

abstract: For multiple species to stably coexist, it is necessary that, as species increase in abundance, they suffer from Conspecific Negative Density Dependence (CNDD)1. For trees, there is ample evidence for such negative effects of abundance on the survival and frequency of juveniles, typically on small spatial scales2-11. Despite this short distance "repulsion" of juveniles, adult trees are generally spatially aggregated12-16, and there is little evidence that CNDD acting on juveniles propagates to the adult stage1,2,17, casting doubt on its importance for coexistence. However, evidence of aggregation was previously obtained by comparing the spatial distribution of adults to a random placement across the landscape12,13, ignoring dispersal limitation. Here we show that, when compared to the predictions of a calibrated null model of stochastic birth, death and limited dispersal, the adults of dozens of tropical forest species are almost ubiquitously and strongly overdispersed, often up to distances of ~100 meters. We also show that such strong overdispersion can only occur if CNDD considerably exceeds Heterospecific Negative Density Dependence, creating stabilizing niche differences, which are an important requirement for stable coexistence. Together these findings suggest that CNDD propagates from juveniles to adults, strongly influencing adult spatial distribution. Furthermore, these results refine our view of the fundamental nature of species spatial distributions, a key interest in ecology12,18-20, and demonstrate the power of using limited dispersal null models to detect biotic interactions and habitat associations from spatial distributions.


title: Patterns of item nonresponse behavior to survey questionnaires are systematic and have a genetic basis

abstract: Response to survey questionnaires is vital for social and behavioral research, and most analyses assume full and accurate response by survey participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behavior across 109 questionnaire items from the UK Biobank (UKB) (N=360,628). Phenotypic factor scores for two participant-selected nonresponse answers, "Prefer not to answer" (PNA) and "I dont know" (IDK), each predicted participant nonresponse in follow-up surveys, controlling for education and self-reported general health. We performed genome-wide association studies on these factors and identified 39 genome-wide significant loci, and further validated these effects with polygenic scores in an independent study (N=3,414), gaining information that we could not have had from phenotypic data alone. PNA and IDK were highly genetically correlated with one another and with education, health, and income, although unique genetic effects were also observed for both PNA and IDK. We discuss how these effects may bias studies of traits correlated with nonresponse and how genetic analyses can further enhance our understanding of nonresponse behaviors in survey research, for instance by helping to correct for nonresponse bias.


title: hibayes: An R Package to Fit Individual-Level, Summary-Level and Single-Step Bayesian Regression Models for Genomic Prediction and Genome-Wide Association Studies

abstract: With the rapid development of sequencing technology, the costs of individual genotyping have been reduced dramatically, leading to genomic prediction and genome-wide association studies being widely promoted and used to predict the unknown phenotypes and to locate causal or candidate genes for animal and plant economic traits and, increasingly, for human diseases. Developing newly advanced statistical models to improve accuracy in predicting and locating for the traits with various genetic architectures has always been a hot topic in those two research domains. The Bayesian regression model (BRM) has played a crucial role in the past decade, and it has been used widely in relevant genetic analyses owing to its flexible model assumptions on the unknown genetic architecture of complex traits. To fully utilize the available data from either a self-designed experimental population or a public database, statistical geneticists have constantly extended the fitting capacity of BRM, and a series of new methodologies have been proposed for different application scenarios. Here we introduce hibayes, which is the only one tool that can implement three types of Bayesian regression models. With the richest methods achieved thus far, it covers almost all the functions involved in genetic analyses for genomic prediction and genome-wide association studies, potentially addressing a wide range of research problems, while retaining an easy-to-use and transparent interface. We believe that hibayes will facilitate the researches conducted by human geneticists, as well as plant and animal breeders. The hibayes package is freely available from CRAN at https://cran.r-project.org/package=hibayes.


title: An optimized method to infer relatedness up to the 5th degree from low coverage ancient human genomes

abstract:
BackgroundCurrent state of art kinship analysis is capable to infer relatedness up to the 5-6th degree from deeply sequenced DNA if the proper reference population is known. Low coverage, partially genotyped, degraded archaic (or forensic) DNA and often unavailable or unknown reference population poses additional challenges, hence kinship analysis from low coverage archaic sequences so far has been possible up to the second degree with large uncertainties.

ResultsWe performed extensive simulations to identify and correct the main factors of bias in kinship analysis from low coverage data. As a result, we introduce a new metric for correction and offer a guideline, which overcomes the difficulties associated with low coverage samples. We validated our methodology on experimental modern and archaic data with widely different genome coverages (0.12x-11.9x) using samples with known family relations and known or unknown population structure. Out of 2526 ancient individuals from the REICH data set we confirmed all 96 indicated, and identified 303 new relatives additionally.

ConclusionWith the proposed workflow we provide the necessary additional tools to calculate the corrected kinship coefficient from the commonly used genome data formats. Our methodology allows to reliably identify relatedness up to the 4-5th degree from variable/low coverage archaic (or badly degraded forensic) WGS genome data.


title: An evolutionarily conserved mechanism for control the translation of long proteins

abstract:
Length is one of the key features of mRNA, varying from dozens to thousands of nucleotides. However, the contribution of length to proteome and its underlying mechanism are largely unknown. Here we show that the translation of long mRNA is regulated by the evolutionarily conserved mcm5s2U modification of tRNA. Loss of mcm5s2U modification results in decreased expression of long proteins in Arabidopsis, budding yeast, and humans. Mechanistically, the mcm5s2U modification facilitates ribosome loading on long mRNAs. Interestingly, the mcm5s2U modification is dynamically modulated to maintain long protein homeostasis during stress responses and cancer metastasis. Furthermore, gene ontology analysis reveals that long proteins are enriched in various conserved biological processes including immunity and DNA repair. Our study suggests that tRNA modification is a general mechanism for control the translation of long proteins and highlights the importance of mRNA length in shaping proteome.

HighlightO_LImcm5s2U of tRNA is required for immunity and DNA repair
C_LIO_LImcm5s2U of tRNA is required for long protein expression
C_LIO_LImcm5s2U facilitate ribosome loading on long mRNAs
C_LIO_LILong proteins are involved in various conserved biological processes
C_LI

category: biochemistry


title: Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data

abstract: We present LC-MS2Struct, a machine learning framework for structural annotation of small molecule data arising from liquid chromatography-tandem mass spectrometry (LC-MS2) measurements. LC-MS2Struct jointly predicts the annotations for a set of mass spectrometry features in a sample, using a novel structured prediction model trained to optimally combine the output of state-of-the-art MS2 scorers and observed retention orders. We evaluate our method on a dataset covering all publicly available reversed phase LC-MS2 data in the MassBank reference database, including 4327 molecules measured using 18 different LC conditions from 16 contributors, greatly expanding the chemical analytical space covered in previous multi-MS2 scorer evaluations. LC-MS2Struct obtains significantly higher annotation accuracy than earlier methods and improves the annotation accuracy of state-of-the-art MS2 scorers by up to 106%. The use of stereochemistry-aware molecular fingerprints improves prediction performance, which highlights limitations in existing approaches and has strong implications for future computational LC-MS2 developments.


title: Computer vision for assessing species color pattern variation from web-based community science images

abstract: Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (Plethodon cinereus). We used an ensemble convolutional neural network model to analyze this polymorphism in 20,318 iNaturalist images. Our model was highly accurate ([~]98%) despite image heterogeneity. We used the resulting annotations to document extensive niche overlap between morphs, but wider niche breadth for striped morphs at the range-wide scale. Our work showcases key design principles for using machine learning with heterogeneous community science image data to address questions at an unprecedented scale.


title: Getting Personal with Epigenetics: Towards Machine-Learning-Assisted Precision Epigenomics

abstract: Epigenetic modifications are dynamic control mechanisms involved in the regulation of gene expression. Unlike the DNA sequence itself, they vary not only between individuals but also between different cell types of the same individual. Exposure to environmental factors, somatic mutations, and ageing contribute to epigenomic changes over time, which may constitute early hallmarks or causal factors of disease. Epigenetic changes are reversible and, therefore, promising therapeutic targets. However, mapping efforts to determine an individuals cell-type-specific epigenome are constrained by experimental costs. We developed eDICE, an attention-based deep learning model, to impute epigenomic tracks. eDICE achieves improved overall performance compared to previous models on the reference Roadmap epigenomes. Furthermore, we present a proof of concept for the imputation of personalised epigenomic measurements on the ENTEx dataset, where eDICE correctly predicts individual- and cell-type-specific epigenetic patterns. This case study constitutes an important step towards robustly employing machine-learning-based approaches for personalised epigenomics.


title: Improved structural variant discovery in hard-to-call regions using sample-specific string detection from accurate long reads

abstract:
Structural variants (SVs) account for a large amount of sequence variability across genomes and play an important role in human genomics and precision medicine. Despite intense efforts over the years, the discovery of SVs in individuals remains challenging due to the diploid and highly repetitive structure of the human genome, and by the presence of SVs that vastly exceed sequencing read lengths. However, the recent introduction of low-error long-read sequencing technologies such as PacBio HiFi may finally enable to overcome these barriers. Here we present SVDSS, a novel hybrid method for discovery of SVs from long-read sequencing technologies (e.g., PacBio HiFi) that combines and effectively leverages mapping-free, mapping-based and assembly-based methodologies for overall superior SV discovery performance. Our experiments on several human samples show that SVDSS outperforms state-of-the-art mapping-based methods for discovery of insertion and deletion SVs in PacBio HiFi reads and achieves significant improvements in calling SVs in repetitive regions of the genome.

SVDSS is open source and publicly available at: https://github.com/Parsoa/SVDSS


title: Near-atomic Structure of the Cytoplasmic Ring of the Xenopus laevis Nuclear Pore Complex

abstract:
The nuclear pore complex (NPC) mediates nucleocytoplasmic shuttling. Here we present single-particle cryo-EM structure of the cytoplasmic ring (CR) from the Xenopus laevis NPC at 4.1-4.7 [A] resolutions. The structure of an N-terminal domain of Nup358 was resolved at 3.0 [A], facilitating identification of five Nup358 molecules in each CR subunit. Aside from unveiling the assembly details of the two Y-shaped multicomponent complexes (Y complexes) in each CR subunit, the improved resolutions reveal the C-terminal fragment of Nup160 to be an organizing center at the vertex of each Y complex. Our structures show that the scaffold of a CR subunit comprises five Nup358, two Nup205 and two Nup93 molecules in addition to the previously characterized Y complexes.

One-Sentence SummaryImproved resolutions of the cytoplasmic ring (CR) of the Xenopus laevis nuclear pore complex reveal that five Nup358 molecules, together with two copies of interweaved Nup205, Nup93 and Y complexes, constitute the scaffold of each CR subunit.


title: Solution structure of the phosphatidylinositol 3-phosphate binding domain from the Legionella effector SetA

abstract: Legionella pneumophila is a facultative intracellular pathogen that causes Legionnaires disease or Pontiac fever in humans upon accidental inhalation of Legionella-contaminated aerosols. During infection, L. pneumophila secretes more than 300 effectors into the host for the biogenesis of a replication-permissive niche, known as the Legionella containing vacuole (LCV). Among these, a large number of effectors harbor protein domains that recognize specific phosphoinositide (PI) lipids and mediate the anchoring of these effectors to the surface of LCV or other host membrane-bound organelles. The Legionella effector SetA contains a unique C-terminal domain (SetA-CTD) that has been shown to specifically bind with phosphatidylinositol-3-phosphate (PI(3)P) and target SetA to endosomes and LCVs. Here, we report the NMR solution structure of SetA-CTD, which mainly comprises a four -helix bundle. The structure reveals a basic pocket at one end of the -helix bundle for PI(3)P binding and two hydrophobic loops for membrane insertion. Mutations of key residues involved in lipid binding result in the loss of SetA in membrane association and endosomal localization. Structural comparison with other PI(3)P-binding domains highlights a general theme applied by multiple families of phosphoinositide-binding domains across species.


title: RNA triplex structures revealed by WAXS-driven MD simulations

abstract: RNA triple helices are commonly observed tertiary motifs that are increasingly associated with critical biological functions, including signal transduction. Because the recognition of their biological importance is relatively recent, their full range of structures and function has not yet been elucidated. The integration of solution wide-angle X-ray scattering (WAXS) with data-driven molecular dynamics (MD) simulations, described here, provides a new way to capture the structures of major-groove RNA triplexes that evade crystallographic characterization. This method yields excellent agreement between measured and computed WAXS profiles, and allows for an atomically detailed visualization of these motifs. Using correlation maps, the relationship between well-defined features in the scattering profiles and real space characteristics of RNA molecules is easily defined, including the subtle conformational variations in the double-stranded RNA upon the incorporation of a third strand by base-triples. This readily applicable approach provides unique insight into some of the interactions that stabilize RNA tertiary structure and enable function.


title: In silico drug design of benzothiadiazine derivatives interactingwith bilayer cell membranes

abstract: The use of drugs derived from benzothiadiazine, a bicyclic heterocyclic benzene derivative, has become a widespread treatment for diseases such as hypertension, low blood sugar or the human immunodeficiency virus, among others. In this work we have investigated the interactions of benzothiadiazine and several selected derivatives designed in silico, with the basic components of cell membranes and solvents such as phospholipids, cholesterol and water. The analysis of the mutual microscopic interactions is of central importance to elucidate the local structure of benzothiadiazine as well as the mechanisms responsible for the distribution and access of benzothiadiazine to the interior of the cell. We have performed molecular dynamics simulations of benzothiadiazine and its derivatives embedded in a model zwitterionic bilayer membrane made by phospholipids dioleoylphosphatidylcholine, 1,2-dioleoyl-sn-glycero-3-phosphoserine and cholesterol inside aqueous potassium chloride solution in order to systematically examine microscopic interactions of benzothiadiazine derivatives with the cell membrane at liquid-crystalline phase conditions. From data obtained through radial distribution functions, time dependent hydrogen-bond lengths and potentials of mean force based on reversible work calculations, we have observed that benzothiadiazine derivatives have a strong affinity to stay at the cell membrane interface although their solvation characterisitics can vary significantly: they can be fully solvated by water in short periods of time or continuously attached to specific lipid sites during intervals of 10-70 ns. Furthermore, benzothiadiazines are able to bind lipids and cholesterol chains by means of single and double hydrogen-bonds of different characteristic lengths between 1.6 and 2.1 [A].


title: A pili-driven bacterial turbine

abstract:
Work generated by self-propelled bacteria can be harnessed with the help of microdevices. Such nanofabricated microdevices, immersed in a bacterial bath, may exhibit unidirectional rotational or translational motion. Swimming bacteria that propel with the help of actively rotating flagella are a prototypical example of active agents that can power such microdevices.

In this work, we propose a computational model of a micron-sized turbine powered by bacteria that rely on active type IV pili appendages for surface-associated motility. We find that the turbine can rotate persistently over a time scale that significantly exceeds the characteristic times of the single cell motility. The persistent rotation is explained by the collective dynamics of multiple pili of groups of cells attaching to and pulling on turbine. Furthermore, we show that the turbine can rotate permanently in the same direction by altering the pili binding to the turbine surface in an asymmetric fashion. We thus can show that by changing the adhesive properties of the turbine while keeping its symmetric geometry, we can still break the symmetry of its rotation.

Altogether, this study widely expands the range of bacteria that can be used to power nanofabricated microdevices, and, due to high pili forces generated by pili retraction, promises to push the harnessed work by several orders of magnitude.


title: Glutathione in the nucleus accumbens regulates motivation to exert reward-incentivized effort

abstract: Emerging evidence is implicating mitochondrial function and metabolism in the nucleus accumbens in motivated performance. However, the brain is vulnerable to excessive oxidative insults resulting from neurometabolic processes and whether antioxidant levels in the nucleus accumbens contribute to motivated performance is not known. Here, we identify a critical role for glutathione (GSH), the most important endogenous antioxidant in the brain, in motivation. Using proton magnetic resonance spectroscopy (1H-MRS) at ultra-high field in both clinical and preclinical populations, we establish that higher accumbal GSH levels are highly predictive of better, and particularly steady performance over time in effort-related tasks. Causality was established in preclinical in vivo experiments that, first, showed that down-regulating GSH levels through micro-injections of the GSH synthesis inhibitor buthionine sulfoximine in the nucleus accumbens impaired effort-based reward-incentivized performance. In addition, systemic treatment with the GSH precursor N-acetyl-cysteine (NAC) increased accumbal GSH levels and led to improved performance, potentially mediated by a cell-type specific shift in glutamatergic inputs to accumbal medium spiny neurons. Our data indicate a close association between accumbal GSH levels and individuals capacity to exert reward-incentivized effort over time. They also suggest that improvement of accumbal antioxidant function may be a feasible approach to boost motivation.


title: FiNN: A toolbox for neurophysiological network analysis

abstract:
In recent years, neuroscience has seen a shift from localist approaches to network-wide investigations of brain function. Neurophysiological signals across different spatial and temporal scales provide an informative insight into neural communication. However, additional methodological considerations arise when investigating network-wide brain dynamics rather than local effects. Specifically, larger amounts of data, investigated across a higher dimensional space, are necessary.

Here, we present FiNN (Find Neurophysiological Networks), a novel toolbox for the analysis of neurophysiological data with a focus on functional and effective connectivity. FiNN provides a wide range of data processing methods, introduces new methodological developments to acquire efficient and reliable connectivity estimates that build on already existing concepts, and statistical and visualization tools to facilitate inspection of connectivity estimates and the resulting metrics of brain dynamics. The toolbox is freely available in Python (https://github.com/neurophysiological-analysis/FiNN), and complemented by online documentation (https://neurophysiological-analysis.github.io/FiNN/).

To highlight the properties of our toolbox, we evaluated FiNN against a number of established frameworks on both a conceptual and an implementation level. We found FiNN to require much less processing time and memory than other toolboxes. In addition, FiNN adheres to a design philosophy of easy access and modifiability, while providing efficient data processing implementations. Since the investigation of network-level neural dynamics is experiencing increasing interest, we place FiNN at the disposal of the neuroscientific community as open-source software.

Highlights- Investigation of network-wide brain dynamics requires specialized software.
- We provide a toolbox to ease the pre-processing and analysis steps of the investigation.
- FiNN requires less processing time and memory in comparison to other toolboxes.
- Extensive documentation facilitates usage by users from various technical backgrounds.


title: Ultrahigh-throughput directed evolution of a metal-free α/β-hydrolase with a Cys-His-Asp triad into an efficient phosphotriesterase

abstract:
The recent massive release of new, man-made substances into the environment requires bioremediation, but a very limited number of enzymes evolved in response are available. When environments have not encountered the potentially hazardous materials in their evolutionary history, existing enzymes have to be repurposed. The recruitment of accidental, typically low-level promiscuous activities provides a head start that, after gene duplication, can adapt and provide a selectable advantage. This evolutionary scenario raises the question whether it is possible to adaptively improve the low-level activity of enzymes recruited from non- (or only recently) contaminated environments quickly to the level of evolved bioremediators.

Here we address the evolution of phosphotriesterases (enzymes for hydrolysis of organophosphate pesticides or chemical warfare agents) in such a scenario: In a previous functional metagenomics screening we had identified a promiscuous phosphotriesterase activity of the /{beta}-hydrolase P91, with an unexpected Cys-His-Asp catalytic triad as the active site motif. We now probe evolvability of P91 using ultrahigh-throughput screening in microfluidic droplets, and test for the first time whether the unique catalytic motif of a cysteine-containing triad can adapt to achieve rates that rival existing phosphotriesterases. These mechanistically distinct enzymes achieve their high rates based on catalysis involving a metal-ion cofactor. A focussed, combinatorial library of P91 (> 105 members) was screened on-chip in microfluidic droplets by quantification of the reaction product, fluorescein. Within only two rounds of evolution P91s phosphotriesterase activity was increased {approx} 400-fold to a kcat/KM of {approx} 106 M-1s-1, matching the catalytic efficiencies of naturally evolved metal-dependent phosphotriesterases. In contrast to its homologue acetylcholinesterase that suffers suicide inhibition, P91 shows fast de-phosphorylation rates and is rate-limited by the formation of the covalent adduct rather than by its hydrolysis. Our analysis highlights how the combination of focussed, combinatorial libraries with the ultrahigh throughput of droplet microfluidics can be leveraged to identify and enhance mechanistic strategies that have not reached high efficiency in Nature, resulting in alternative reagents with a novel catalytic machinery.

GRAPHICAL ABSTRACT

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title: Lack of evidence for participation of TMEM150c/TENTONIN3 in sensory mechanotransduction.

abstract: The membrane protein TMEM150c has been proposed to form a mechanosensitive ion channel that is required for normal proprioceptor function. Here we examined whether expression of TMEM150c in neuroblastoma cells lacking Piezo1 is associated with the appearance of mechanosensitive currents. Using three different modes of mechanical stimuli, indentation, membrane stretch and substrate deflection we could not evoke mechanosensitive currents in cells expressing TMEM150c. We next asked if TMEM150c is necessary for the normal mechanosensitivity of cutaneous sensory neurons. We used an available mouse model in which the Tmem150c locus was disrupted through the insertion of a LacZ cassette with a splice acceptor that should lead to transcript truncation. Analysis of these mice indicated that ablation of the Tmem150c gene was not complete in sensory neurons of the dorsal root ganglia (DRG). Using a Crispr/cas9 strategy we made a second mouse model in which a large part of the Tmem150c gene was deleted and established that these Tmem150c-/- mice completely lack TMEM150c protein in the DRGs. We used an ex vivo skin nerve preparation to characterize the mechanosenstivity of mechanoreceptors and nociceptors in the glabrous skin of the Tmem150c-/- mice. We found no quantitative alterations in the physiological properties of any type of cutaneous sensory fiber in Tmem150c-/- mice. Since it has been claimed that TMEM150c is required for normal proprioceptor function we made a quantitative analysis of locomotion in Tmem150c-/- mice. Here again we found no indication that there was altered gait in Tmem150c-/- mice compared to wild type controls. In summary, we conclude that existing mouse models that have been used to investigate TMEM150c function in vivo are problematic. Furthermore, we could find no evidence that TMEM150c forms a mechanosensitive channel or that it is necessary for the normal mechanosensitivity of cutaneous sensory neurons.