bluuebunny/crossref_metadata_2025 huggingface dataset:
Creating a thermostable beta-glucuronidase switch for homogeneous immunoassay by disruption of conserved salt bridges at diagonal interfaces
Authors: Zhu Bo , Qian Cheng , Tang Haoxuan , Kitaguchi Tetsuya , Ueda Hiroshi
Published: May 2022

The Escherichia coli beta-glucuronidase (GUS) has been used as a reporter enzyme in molecular biology and has been engineered to enzyme switches for the development of homogeneous biosensors. Here, we developed a thermostable GUS enzyme switch from a thermostable GUS mutant TR3337 by disrupting a conserved salt bridge (H514-E523) between the diagonal subunits of its homotetramer. A combinatorial library (240 variants) was screened by a novel high-throughput strategy, and a mutant DLW (H514D/M516L/Y517W) was found to be a functional enzyme switch in a caffeine-recognizing immunosensor. The molecular dynamics simulations were performed to predict the topology change around position 514, and the sidechain flip of D514 (repulsion with E523) was observed in the DLW mutant. Up to 1.8-fold of the signal-to-background ratio was confirmed when measured at 45 °C, which makes the DLW mutant a versatile tool for developing the thermostable immunosensors for in vitro and in cellulo applications.

Table of contents graphic
The synergistic effects of the VH families and CH regions of multimeric IgM on its interaction with FcμR, and antigen
Authors: Ling Wei-Li , Gan Samuel Ken-En
Published: May 2022

As the primary response antibody with increasing interest as a therapeutic antibody format, IgM is also the largest antibody structure among the five major human isotypes. Spontaneously forming pentamer and hexamers, IgM has avidity effects that could compensate for weaker interactions, although steric hindrances can occur for certain epitopes. With recent evidence of the heavy chain constant region affecting antigen binding and the VH families of the V-regions affecting FcR engagement found on other isotypes, we investigated CDR-grafted Trastuzumab and Pertuzumab VH1-7 IgMs for biolayer interferometry. From our panel of the 14 IgM variants, the V-regions holistically affected FcμR binding, and the IgM C-region modulated Her2 engagements with contributions from the V-regions and influences from protein L binding at the Vκ. These findings revealed the oligomerization effect of IgMs to play a significant role in both FcμR and antigen binding that is distinct from the other isotypes that can guide the development and protein en-gineering of IgM therapeutics.
DEGRONOPEDIA - a web server for proteome-wide inspection of degrons
Authors: Szulc Natalia A. , Stefaniak Filip , Piechota Małgorzata , Cappannini Andrea , Bujnicki Janusz M. , Pokrzywa Wojciech
Published: May 2022

The ubiquitin-proteasome system is a proteolytic pathway that removes damaged and unwanted proteins. Their selective turnover is initiated by ubiquitin (Ub) attachment, mainly by Ub ligases that recognize substrates through their short linear motifs termed degrons. A degradation-targeting degron comprises a nearby Ub-modified residue and an intrinsically disordered region (IDR) involved in interaction with the proteasome. Degron-signaling has been studied over the last decades, yet there are no resources for systematic screening of degron sites to facilitate studies on their biological significance, such as targeted protein degradation approaches. To bridge this gap, we developed DEGRONOPEDIA, a web server that allows exploration of degron motifs in the proteomes of seven model organisms and maps these data to Lys, Cys, Thr, and Ser residues that can undergo ubiquitination and to IDRs proximal to them, both in sequence and structure. The server also reports the post-translational modifications and pathogenic mutations within the degron and its flanking regions, as these can modulate the degron’s accessibility. Degrons often occur at the amino or carboxyl end of a protein substrate, acting as initiators of the N-/C-degron pathway, respectively. Therefore, since they may appear following the protease cleavage, DEGRONOPEDIA simulate sequence nicking based on experimental data and theoretical predictions and screen for emerging degron motifs. Moreover, we implemented machine learning to predict the stability of the N-/C-termini, facilitating the identification of substrates of the N-/C-degron pathways. We are confident that our tool will stimulate research on degron-signaling providing output information in a ready-to-validate context. DEGRONOPEDIA can be freely accessed atdegronopedia.com.
A social media-based framework for quantifying temporal changes to wildlife viewing intensity: Case study of sea turtles before and during COVID-19
Authors: Papafitsoros Kostas , Adam Lukáš , Schofield Gail
Published: May 2022

Documenting how human pressure on wildlife changes over time is important to minimise potential adverse effects through implementing appropriate management and policy actions; however, obtaining objective measures of these changes and their potential impacts is often logistically challenging, particularly in the natural environment. Here, we developed a modular stochastic model that infers the ratio of actual viewing pressure on wildlife in consecutive time periods (years) using social media, as this medium is widespread and easily accessible. Pressure was calculated from the number of times individual animals appeared in social media in pre-defined time windows, accounting for time-dependent variables that influence them (e.g. number of people with access to social media). Formulas for the confidence intervals of viewing pressure ratios were rigorously developed and validated, and corresponding uncertainty was quantified. We applied the developed framework to calculate changes to wildlife viewing pressure on loggerhead sea turtles (Caretta caretta) at Zakynthos island (Greece) before and during the COVID-19 pandemic (2019-2021) based on 2646 social media entries. Our model ensured temporal comparability across years of social media data grouped in time window sizes, by correcting for the interannual increase of social media use. Optimal sizes for these windows were delineated, reducing uncertainty while maintaining high time-scale resolution. The optimal time window was around 7-days during the peak tourist season when more data were available in all three years, and >15 days during the low season. In contrast, raw social media data exhibited clear bias when quantifying changes to viewing pressure, with unknown uncertainty. The framework developed here allows widely-available social media data to be used objectively when quantifying temporal changes to wildlife viewing pressure. Its modularity allowed viewing pressure to be quantified for all data combined, or subsets of data (different groups, situations or locations), and could be applied to any site supporting wildlife exposed to tourism.
Competition-cooperation in the chemoautotrophic ecosystem of Movile Cave – first metagenomic approach on sediments
Authors: Chiciudean Iulia , Russo Giancarlo , Bogdan Diana Felicia , Levei Erika Andrea , Faur Luchiana , Hillebrand-Voiculescu Alexandra , Moldovan Oana Teodora , Banciu Horia Leonard
Published: May 2022

Background

Movile Cave (Dobrogea, SE Romania) hosts a subterranean chemoautotrophically-based ecosystem supported by a sulfidic thermal aquifer analogous to the deep-sea hydrothermal ecosystems. Our current understanding of Movile Cave microbiology has been confined to the thermal water proximity (no more than 2 m distant), with most studies focusing on the water-floating mat, which likely acts as the primary production powerhouse in this sulfidic ecosystem. To gain more insightful information on the functioning of the sulfidic Movile Cave ecosystem, we employed a metagenomics-resolved approach to reveal the microbiome diversity, metabolic potential, and interactions and infer its roles within the food webs in the sediments beyond the sulfidic thermal waters.

Results

A customized bioinformatics pipeline led to the recovery of 106 high-quality metagenome-assembled genomes from 7 cave sediment metagenomes. Assemblies’ taxonomy spanned 19 bacterial and three archaeal phyla withAcidobacteriota, Chloroflexota, Proteobacteria, Planctomycetota, Ca. Patescibacteria,Thermoproteota, Methylomirabilota, andCa. Zixibacteria as prevalent phyla. Functional gene analyses allowed prediction of CO2fixation, methanotrophy, sulfur and ammonia oxidation as possibly occurring in the explored sediments. Species Metabolic Coupling Analysis of metagenome-scale metabolic models revealed the highest competition-cooperation interactions in the sediments collected at the farthest distance from the sulfidic water. As a result of simulated metabolic interactions, autotrophs and methanotrophs were hypothesized as major donors of exchanged metabolites in the sediment communities. Cross-feeding dependencies were assumed only towards ‘currency’ molecules and inorganic compounds (O2, PO43-, H+, Fe2+, Cu2+) in the sediment nearby sulfidic water, whereas hydrogen sulfide and methanol are predictably traded exclusively among communities dwelling in the distant gallery.

Conclusions

These findings suggest that the primary production potential of the Movile Cave expands way beyond its hydrothermal waters, enhancing our understanding of ecological interactions inside chemolithoautotrophically based subterranean ecosystems and their functioning.
Systematic evaluation of high level visual deficits and lesions in posterior cerebral artery stroke
Authors: Robotham Ro Julia , Rice Grace E , Leff Alex P , Lambon Ralph Matthew A , Starrfelt Randi
Published: May 2022

Knowledge about the consequences of stroke on high level vision comes primarily from single case studies of patients selected based on their behavioural profiles with deficits in the recognition of a specific visual category such as faces or words. There are, however, no systematic, detailed, large-scale evaluations of the more typical clinical behavioural and lesion profiles of impairments in high level vision that may follow posterior cerebral artery (PCA) stroke. These goals were met by the current study through the data collected in the Back of the Brain (BoB) project: to date, the largest (N=64) and most detailed examination of patients with cortical PCA strokes selected based on lesion location rather than behavioural symptoms.

We present here two complementary analyses of the structural neuroimaging data and key indices of behavioural performance with the visual processing words, objects and faces: (1) a multivariate multiple regression analysis to establish the relationships between lesion volume, lesion laterality or the presence of a bilateral lesion with performance on words, objects and faces; and, (2) a voxel-based correlational method (VBCM) analysis to establish whether there are distinct or separate regions within the PCA territory that underpin the visual processing of these categories.

In contrast to the characterization of specific stroke syndromes like pure alexia or prosopagnosia in the literature, most patients in our cohort showed more general deficits in high level vision (n=22) or no deficits at all (n=21). Category-selective deficits were rare (n=6), and were only found for words, which, interestingly could follow left or right hemisphere lesions. The lesion analyses mainly confirmed the pattern reported in more selective cases: word recognition impairments are associated with a left-sided pattern of damage and face recognition deficits with a bilateral albeit right-dominant lesion pattern. Importantly, however, both general and more selective impairment may follow from left or right unilateral as well as bilateral lesions.

While the findings provide partial support for the relative laterality of posterior brain regions supporting reading in the left and, to a lesser extent, face processing in the right hemisphere, the results suggest that both hemispheres are involved in the visual processing of faces, words and objects. This has ramifications for researchers studying the healthy brain and for clinicians working with patients with PCA stroke. Clinicians are recommended to carry out formal assessment of face, word and object recognition as most patients are expected to present with a mixed picture of deficits.
Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests
Authors: Frank Filipp , Keen Meredith M. , Rao Anuradha , Bassit Leda , Liu Xu , Bowers Heather B. , Patel Anamika B. , Cato Michael L. , Sullivan Julie A. , Greenleaf Morgan , Piantadosi Anne , Lam Wilbur A. , Hudson William H. , Ortlund Eric A.
Published: May 2022

Widespread and frequent testing is critical to prevent the spread of COVID-19, and rapid antigen tests are the diagnostic tool of choice in many settings. With new viral variants continuously emerging and spreading rapidly, the effect of mutations on antigen test performance is a major concern. In response to the spread of variants the National Institutes of Health’s Rapid Acceleration of Diagnostics (RADx®) initiative created a Variant Task Force to assess the impact of emerging SARS-CoV-2 variants on in vitro diagnostic testing. To evaluate the impact of mutations on rapid antigen tests we developed a lentivirus-mediated mammalian surface-display platform for the SARS-CoV-2 Nucleocapsid protein, the target of the majority of rapid antigen tests. We employed deep mutational scanning (DMS) to directly measure the effect of all possible Nucleocapsid point mutations on antibody binding by 17 diagnostic antibodies used in 11 commercially available antigen tests with FDA emergency use authorization (EUA). The results provide a complete map of the antibodies’ epitopes and their susceptibility to mutational escape. This approach identifies linear epitopes, conformational epitopes, as well as allosteric escape mutations in any region of the Nucleocapsid protein. All 17 antibodies tested exhibit distinct escape mutation profiles, even among antibodies recognizing the same folded domain. Our data predict no vulnerabilities of rapid antigen tests for detection of mutations found in currently and previously dominant variants of concern and interest. We confirm this using the commercial tests and sequence-confirmed COVID-19 patient samples. The antibody escape mutation profiles generated here serve as a valuable resource for predicting the performance of rapid antigen tests against past, current, as well as any possible future variants of SARS-CoV-2, establishing the direct clinical and public health utility of our system. Further, our mammalian surface-display platform combined with DMS is a generalizable platform for complete mapping of protein-protein interactions.
Substantial seagrass blue carbon pools in the southwestern Baltic Sea are spatially heterogeneous, mostly autochthonous, and include relics of terrestrial peatlands
Authors: Stevenson Angela , Corcora Tadhg C. Ó , Hukriede Wolfgang , Schubert Philipp R. , Reusch Thorsten B.H.
Published: May 2022

Seagrass meadows have a disproportionally high organic carbon (Corg) storage potential (‘blue carbon’) within their sediments and thus can play an important role in climate change mitigation via their conservation and restoration. However, high spatial heterogeneity is observed in Corg, with wide differences seen globally (i.e. tropical vs temperate), regionally, and even locally (within a seagrass meadow). Consequently, it is difficult to determine their contributions to the national remaining carbon dioxide (CO2) budget without introducing a large degree of uncertainty.

In order to address this spatial heterogeneity, we sampled 20 locations across the Baltic Sea coast of Germany to quantify carbon stocks and sources inZostera marinaseagrass-vegetated and adjacent unvegetated sediments. To predict and integrate the Corginventory in space, we measured the physical (seawater depth, sediment grain size, current velocity at the seafloor, anthropogenic inputs) and biological (seagrass complexity) environment to determine regional (between sites) and local (within site) drivers of Corgvariation.

Here we show that seagrass meadows in the German Baltic Sea constitute a significant Corgstock, storing on average 7,785 ± 679 g C/m2, 13 times greater than meadows from other parts of the Baltic Sea (outside of Germany), and four-fold richer than adjacent unvegetated sediments. Stocks were highly heterogenous; they differed widely between (by 10-fold) and even within (by 3 to 55-fold) sites. At a regional scale (350 km), Corgwas controlled by seagrass complexity, fine sediment fraction, and seawater depth. Autochthonous material (seagrass-derived and large infauna) contributed to 78% of the total Corgin vegetated sediments and the remaining 22% originated from allochthonous sources (phytoplankton, drift algaePilayella littoralis, and other macroalgae). However, relic terrestrial peatland material, deposited during the last deglaciation 5,806 and 5,095 years BP, was an unexpected and significant source of Corg.

Collectively, German seagrass meadows in the Baltic Sea are preventing 8.14 Mt of future CO2emissions. Because Corgis mostly produced on site, and not imported from outside the boundaries of the meadow, the richness of this pool may be contingent on seagrass habitat health. Disturbance of this Corgstock could act as a source of CO2emissions. However, the high spatial heterogeneity seen across the region warrant site-specific investigations to obtain accurate estimates of blue carbon, and a need to consider millennial timescale deposits of Corgbeneath seagrass meadows in Germany and potentially other parts of the southwestern Baltic Sea.
mNeonGreen-tagged fusion proteins and nanobodies reveal localization of tropomyosin to patches, cables, and contractile actomyosin rings in live yeast cells
Authors: Hatano Tomoyuki , Lim Tzer Chyn , Billault-Chaumartin Ingrid , Dhar Anubhav , Gu Ying , Massam-Wu Teresa , Adishesha Sushmitha , Springall Luke , Sivashanmugam Lavanya , Scott William , Mishima Masanori , Martin Sophie G , Oliferenko Snezhana , Palani Saravanan , Balasubramanian Mohan K.
Published: May 2022

Tropomyosins are structurally conserved α-helical coiled-coil dimeric proteins that bind along the length of filamentous actin (F-actin) in fungi and animals. Tropomyosins play essential roles in the stability of actin filaments in non-muscle cells and are essential for calcium regulation of myosin II contractility in the muscle. Despite the crucial role of tropomyosin in actin cytoskeletal regulation, in vivo investigations of tropomyosin are limited, mainly due to the suboptimal live cell imaging tools currently available in many organisms. Here, we report mNeon-Green (mNG) tagged tropomyosin, with native promoter and linker length configuration, that clearly reports tropomyosin localization and dynamics in Schizosaccharomyces pombe (Cdc8), Schizosaccharomyces japonicus (Cdc8), and Saccharomyces cerevisiae (Tpm1 and Tpm2), in vivo and in isolated S. pombe cell division apparatuses. We extended this approach to also visualize the mammalian TPM2 isoform. Finally, we generated a camelid-nanobody against S. pombe Cdc8, which mimics the localization of mNG-Cdc8 in vivo without significantly influencing cell growth and dynamics of actin cytoskeleton. Using these tools, we report the presence of tropomyosin in previously unappreciated patch-like structures in fission and budding yeasts, show flow of tropomyosin (F-actin) cables to the cytokinetic actomyosin ring, and identify rearrangements of the actin cytoskeleton during mating. These powerful tools and strategies will aid better analyses of tropomyosin and actin cables in vivo.
Computational modelling of local fluctuations causing transient solvent exposure of protein amides
Authors: Bhakat Soumendranath , Söderhjelm Pär
Published: May 2022

Hydrogen exchange (HX) between protein amides and solvent water molecules can function as a probe for protein dynamics and provide a bridge between the experimental and computational worlds. However, it is important that the underlying assumptions are tested on well-known systems. Here we perform an analysis of a long MD simulation of BPTI, which has previously been used by Persson and Halle to propose a functional definition of the exchange-competent configurations. We find support for the hypothesis that the exchange-competent configurations typically do not constitute a metastable state per se, but rather occur as the outermost tail of the water distribution around a metastable broken state directly identifiable as having a broken intermolecular hydrogen bond and increased solvent-exposure. Furthermore, we estimate the lifetime of these broken states and the probability that exchange-competent configurations occur in them. We have also tested various sampling protocols and their ability to enhance the exploration of the broken states. Computational protocol used in this study can be applied to a broad range of sys-tems to gain valuable insight into the nature of the broken state, although further development is needed to devise a generally applicable quantitative method.
Model metamers illuminate divergences between biological and artificial neural networks
Authors: Feather Jenelle , Leclerc Guillaume , Mądry Aleksander , McDermott Josh H.
Published: May 2022

Deep neural network models of sensory systems are often proposed to learn representational transformations with invariances like those in the brain. To reveal these invariances we generated “model metamers” – stimuli whose activations within a model stage are matched to those of a natural stimulus. Metamers for state-of-the-art supervised and unsupervised neural network models of vision and audition were often completely unrecognizable to humans when generated from deep model stages, suggesting differences between model and human invariances. Targeted model changes improved human-recognizability of model metamers, but did not eliminate the overall human-model discrepancy. The human-recognizability of a model’s metamers was well predicted by their recognizability by other models, suggesting that models learn idiosyncratic invariances in addition to those required by the task. Metamer recognition dissociated from both traditional brain-based benchmarks and adversarial vulnerability, revealing a distinct failure mode of existing sensory models and providing a complementary benchmark for model assessment.
Timed Notch Inhibition drives Photoreceptor fate specification in Human Retinal Organoids
Authors: Chew Shereen H. , Martinez Cassandra , Chirco Kathleen R. , Kandoi Sangeetha , Lamba Deepak A.
Published: May 2022

Purpose

Transplanting photoreceptors from human pluripotent stem cell derived retinal organoids have the potential to reverse vision loss in affected individuals. However, transplantable photoreceptors are only a subset of all cells in the organoids. Hence the goal of our current study was to accelerate and synchronize photoreceptor differentiation in retinal organoids by inhibiting the Notch signaling pathway at different developmental time-points using a small molecule, PF-03084014 (PF).

Methods

Human induced pluripotent stem cell (hiPSC)- and embryonic stem cells (hESC)-derived retinal organoids were treated with 10μM PF for three days at day 45 (D45), D60, D90 and D120 of differentiation. Organoids collected at 14-, 28-, and 42-days post-PF treatment were analyzed for progenitor and photoreceptor markers and Notch pathway inhibition by immunohistochemistry (IHC), quantitative PCR (qPCR) and bulk RNA-seq (n=3-5 organoids from 3 independent experiments).

Results

Retinal organoids collected at 14-days post-PF treatment showed a decrease in progenitor markers (KI67, VSX2, PAX6, and LHX2) and an increase in differentiated pan-photoreceptor markers (OTX2, CRX, and RCVRN) at all organoid stages except D120. PF-treated organoids at D45 and D60 exhibited an increase in cone photoreceptor markers (RXRG and ARR3). PF-treatment at D90 revealed an increase in cone and rod photoreceptors markers (ARR3, NRL, and NR2E3). Bulk RNA-seq analysis mirrored the IHC data and qPCR confirmed Notch effector inhibition.

Conclusions

Timing the Notch pathway inhibition in human retinal organoids to align with progenitor competency stages can yield an enriched population of early cone or rod photoreceptors.
recountmethylation enables flexible analysis of public blood DNA methylation array data
Authors: Maden Sean K. , Walsh Brian , Ellrott Kyle , Hansen Kasper D. , Thompson Reid F. , Nellore Abhinav
Published: May 2022

Thousands of DNA methylation (DNAm) array samples from human blood are publicly available on the Gene Expression Omnibus (GEO), but they remain underutilized for experiment planning, replication, and cross-study and cross-platform analyses. To facilitate these tasks, we augmented our recountmethylation R/Bioconductor package with 12,537 uniformly processed EPIC and HM450K blood samples on GEO as well as several new features. We subsequently used our updated package in several illustrative analyses, finding (1) study ID bias adjustment increased variation explained by biological and demographic variables, (2) most variation in autosomal DNAm was explained by genetic ancestry and CD4+ T-cell fractions, and (3) the dependence of power to detect differential methylation on sample size was similar for each of peripheral blood mononuclear cells (PBMC), whole blood, and umbilical cord blood. Finally, we used PBMC and whole blood to perform independent validations, and we recovered 40-46% of differentially methylated probes (DMPs) between sexes from two previously published epigenome-wide association studies (EWAS).
Single-molecule and super-resolved imaging deciphers membrane behaviour of onco-immunogenic CCR5
Authors: Hunter Patrick , Payne-Dwyer Alex L. , Shaw Michael , Signoret Nathalie , Leake Mark C.
Published: May 2022

The ability of tumors to establish a pro-tumorigenic microenvironment is becoming an important point of investigation in the search for new therapeutics. Tumors form microenvironments in part by the ‘education’ of immune cells attracted via chemotactic axes such as that of CCR5-CCL5. Further, CCR5 upregulation by cancer cells, coupled with its association with pro-tumorigenic features such as drug-resistance and metastasis, has suggested CCR5 as a target for therapeutic inhibition. However, with several conformational “pools” being reported, phenotypic investigations must be capable of unveiling heterogeneity. Addressing this challenge, we performed structured illumination (SIM) and Partially TIRF coupled HILO (PaTCH) microscopy for super-resolution imaging and single-molecule imaging of CCR5 in fixed cells. Determining the positions of super-resolved CCR5 assemblies revealed a non-random spatial orientation. Further, intensity-tracking of assemblies revealed a distribution of molecular stoichiometries indicative of dimeric sub-units independent of CCL5 perturbation. These biophysical methods can provide important insights into the structure and function of onco-immunogenic receptors and a plethora of other biomolecules.

Highlights

We use SIM and novel PaTCH microscopy for precise bioimaging and single-molecule tracking of receptor protein CCR5 in model cell line

By tracking the position of CCR5 assemblies we conclude that they are clustered in the plasma membrane beyond a level expected from a random distribution

We use these high-precision data to determine molecular stoichiometries of CCR5 assemblies
Conserved and variable responses of the HEAT SHOCK FACTOR transcription factor family in maize and Setaria viridis
Authors: Myers Zachary A. , Wootan Clair M. , Liang Zhikai , Zhou Peng , Englehorn Julia , Hartwig Thomas , Springer Nathan M.
Published: May 2022

Responding to the environment is a core aspect of plant growth and development. Mounting an effective response is important for plants to balance growth and survival. The HEAT SHOCK FACTOR (HSF) transcription factor family is a central and required component of plant heat stress responses and acquired thermotolerance. The HSF family has dramatically expanded in plant lineages, often including a repertoire of 20 or more genes. Here we assess the composition and heat responsiveness of the HSF family in Setaria viridis (Setaria), a model C4 panicoid grass, and make targeted comparisons between the HSF families of Setaria and maize. Examples of both conserved and variable expression responses to a heat stress event were observed when comparing the two species. Novel and existing data on chromatin accessibility, histone modifications, and genome-wide DNA binding profiles were utilized to assess the chromatin of HSF family members with distinct responses to heat stress. We observed significant variability for both expression and chromatin state within syntenic and orthologous sets of HSFs between Setaria and maize, as well as between syntenic pairs of maize HSFs retained following its most recent genome duplication event. These observations collectively support a complex scenario of expansion and sub-functionalization within this transcription factor family that has significant untapped potential for better understanding the evolution of large gene families.

Significance Statement

A comparison of the Heat Shock Factor transcription factors in maize and Setaria reveals examples of consistent and variable expression responses to heat stress and provides insights into the role of chromatin in predicting expression responses.
JEDII: Juxtaposition Enabled DNA-binding Interface Identifier
Authors: Nair Sanjana , Madhusudhan M.S.
Published: May 2022

The specific recognition of small stretches of the genomic sequence by their cognate binding protein partners is crucial for various biological processes. Traditionally the prediction of DNA-protein interactions has been treated as two separate problems - one where we predict the most probable DNA sequence that a given protein would bind to and another where we determine the amino acids constituting the DNA binding pocket on a protein. In this study, we introduce JEDII, a template-based method that combines these two aspects of DNA-protein interactions and predicts the residues, nucleotides and amino acids, that would mediate the interaction. Our computational method utilises known structures of DNA-protein complexes in a protocol that superimposes amino acid-nucleotide hydrogen-bonding donor and acceptors atoms on one another to identify the protein-DNA interface. The corner stone of the method is that specificity bestowing hydrogen-bonding interactions are structurally conserved. We validated the accuracy of our procedure on a dataset of 285 DNA-protein complexes where JEDII predicted the cognate DNA sequence with a 62% accuracy. It predicted the DNA-binding amino acids on the protein with 94 % accuracy and an MCC of 0.70. JEDII was also separately compared to other popular methods that predict the cognate DNA sequence and to methods that predict the DNA binding residues. The comparisons were done over four different datasets and JEDII outperformed most methods over all these data sets. JEDII is a robust method following a simple replicable algorithm to determine the molecular basis of DNA-protein specificity and could be instrumental in predicting DNA-protein complexes that are central to key biological phenomena.
The canonical Wnt signaling pathway is not a promising therapeutic target for PNS regeneration enhancement
Authors: Mehta Nikita , Vardy Maia , Elbaz Benayahu
Published: May 2022

PNS injury initiates transcriptional changes in Schwann cells, satellite glial cells and PNS neurons that facilitate regeneration. The signaling pathways that control these transcriptional changes are not fully understood. The canonical Wnt signaling pathway is active during early stages of PNS development, where it controls radial axonal sorting and the onset of PNS myelination. Upon PNS injury, the Wnt signaling pathway is re-activated, suggesting that Wnt signaling plays an important role in PNS regeneration. To explore the potential of the Wnt pathway as a therapeutic target for enhancement of PNS recovery, we used a combination of genetic and pharmacological approaches to either activate or inhibit the Wnt signaling pathway during PNS recovery. We found that manipulating the Wnt signaling pathway does not alter PNS regeneration. Our data suggests that the Wnt signaling pathway is not a strong therapeutic target for the enhancement of PNS regeneration.
Scent mark signal investment predicts fight dynamics in house mice
Authors: Miller Caitlin H. , Haxhillari Klaudio , Hillock Matthew F. , Reichard Tess M. , Sheehan Michael J.
Published: May 2022

Signals mediate competitive interactions by allowing rival assessment, yet are often energetically expensive to produce. Individuals face tradeoffs when deciding when and where to signal, such that over or under-investing in signaling effort can be costly. One of the key mechanisms maintaining signal reliability is via social costs. While the social costs of over-signaling are well-known, the social costs of under-signaling are underexplored, particularly for dynamic signals. In this study we investigate a dynamic and olfactory-mediated signaling system that is ubiquitous among mammals: scent marking. Male house mice territorially scent mark their environment with metabolically costly urine marks. While competitive male mice are thought to deposit abundant scent marks in the environment, we recently identified a cohort of low-marking males that win fights. Whereas there are clear energetic costs to investing in urine signals in mice, we hypothesized that there may be social costs imposed on individuals who under-invest in signaling. Here we find that scent mark investment predicts fight dynamics. Despite fight outcome being unambiguous, aggressive intensity varies considerably across trials. Males that produce fewer scent marks engage in more intense fights that take longer to resolve. This effect appears to be driven by an unwillingness among losers to acquiesce to weakly signaling winners. We therefore find evidence for rival assessment of scent marks as well as social costs to under-signaling, which supports existing hypotheses for the importance of social punishment in maintaining optimal signaling equilibria. Our results further highlight the possibility of diverse signaling strategies in house mice.
Interpreting the fossil record and the origination of birds
Authors: Crouch Nicholas M. A.
Published: May 2022

The fossil record is essential for understanding when lineages originate and their pace of diversification. However, numerous taphonomic biases in the fossil record can hinder interpretation, creating discord between palaeontological and phylogenetic estimates of clade origination dates. Here, I use the recently published Bayesian Brownian Bridge method to infer the age of birds using occurrence data from the Paleobiology Database. I also estimate the age of the speciose sub-clade Telluraves to compare age estimates with previous tip-dating analyses of the same group. Analyses of all birds show place the root age approximately 100 Ma, approximately 26 Myr before the oldest fossil occurrences. Increasing the time bin size from 2.5 to 5 Myr produced significantly older and less precise estimates. Divergence estimates for Telluraves were strikingly consistent with tip-dating analyses, placing origination of the group in the latest Cretaceous. Although these dates are consistent with a hypothesis of Mesozoic origination and Cenozoic diversification, significant diversification was estimated before the end-Cretaceous mass extinction suggesting analyses using pooled species counts may produce spurious results. Overall, these analyses provide further evidence to a growing consensus that several major avian lineages survived the end-Cretaceous mass extinction before diversifying into the most speciose extant tetrapod radiation.
Homeostatic changes maintain the gain control of spinal motoneurones across the lifetime of C57BL/6J mice
Authors: Goltash S , Jensen MH , Dimintiyanova KP , Jensen DB , Lehnhoff J , Moldovan M , Meehan CF
Published: May 2022

Age-related changes in the excitability of spinal motoneurone have been observed in mouse models of neurodegenerative diseases affecting these neurones. How the excitability of spinal motoneurones change with healthy ageing in mice and how this compares with that seen in neurodegenerative diseases is unknown. Therefore, we performed in vivo intracellular recording from identified spinal motoneurones in C57BL/6 mice at three different ages (100, 300-400 and 600-750 days old). Behavioral tests confirmed a linear reduction in motor function across these ages (using the rotorod test).

Significant differences were observed with respect to the features of individual somatic action potential with ageing including a decreased rate of rise and fall in aged mice. Surprisingly, the rate of rise of the action potential at the initial segment was altered in middle aged mice. Immunohistochemical labelling of the axon initial segment of the motoneurones confirmed structural changes occurring at middle age (decreased length and diameter) but returning to the earlier parameters in aged mice. To explore the effects on repetitive firing, this was tested across the age groups which showed surprising little difference as the mice aged, with a similar rheobase and I-f gain across all age groups (with the exception of a lower voltage threshold for action potential initiation in middle-aged mice). However, amplitudes of the after-hyperpolarization and the input resistance were both found to be significantly altered with age.

We conclude that there are changes occurring in the intrinsic properties of spinal motoneurones that control their excitability over the lifetime of mice, although these do not develop in a linear fashion from young to old. We propose that these changes are homeostatic in nature and are able to compensate for one another to maintain a constant gain control across the lifetime.
An electrogenetic toggle switch design
Authors: Grozinger Lewis , Heidrich Elizabeth , Goñi-Moreno Ángel
Published: May 2022

Synthetic biology uses molecular biology to implement genetic circuits that perform computations. These circuits can process inputs and deliver outputs according to predefined rules that are encoded, often entirely, into genetic parts. However, the field has recently begun to focus on using mechanisms beyond the realm of genetic parts for engineering biological circuits. We analyse the use of electrogenic processes for circuit design and present a model for a merged genetic and electrogenetic toggle switch. Computational simulations explore conditions under which bistability emerges in order to identify the circuit design principles for best switch performance. The results provide a basis for the rational design and implementation of hybrid devices that can be measured and controlled both genetically and electronically.
Higher-order interactions shape microbial interactions as microbial community complexity increases
Authors: Morin Manon A. , Morrison Anneliese J. , Harms Michael J. , Dutton Rachel J.
Published: May 2022

Non-pairwise interactions, or higher-order interactions (HOIs), in microbial communities have been claimed to explain the emergent features in microbiomes. Yet, the re-organization of microbial interactions between pairwise cultures and larger communities remains largely unexplored from a molecular perspective but is central to our understanding and further manipulation of microbial communities. Here, we used a bottom-up approach to investigate microbial interaction mechanisms from pairwise cultures up to 4-species communities from a simple microbiome (Hafnia alvei, Geotrichum candidum, Pencillium camemberti and Escherichia coli). Specifically, we characterized the interaction landscape for each species combination involving E. coli by identifying E. coli’s interaction-associated genes using an RB-TnSeq-based interaction assay. We observed a deep reorganization of the interaction-associated genes, with very few 2-species interactions conserved all the way up to a 4-species community and the emergence of multiple HOIs. We further used a quantitative genetics strategy to decipher how 2-species interactions were quantitatively conserved in higher community compositions. Epistasis-based analysis revealed that, of the interactions that are conserved at all levels of complexity, 82% follow an additive pattern. Altogether, we demonstrate the complex architecture of microbial interactions even within a simple microbiome, and provide a mechanistic and molecular explanation of HOIs.
High-resolution neural recordings improve the accuracy of speech decoding
Authors: Duraivel Suseendrakumar , Rahimpour Shervin , Chiang Chia-Han , Trumpis Michael , Wang Charles , Barth Katrina , Lad Shivanand P. , Friedman Allan H. , Southwell Derek G. , Sinha Saurabh R. , Viventi Jonathan , Cogan Gregory
Published: May 2022

Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One promising solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed novel, high-resolution, micro-electrocorticographic (μECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57× higher spatial resolution and 48% higher signal-to-noise ratio compared to standard invasive recordings. This increased signal quality improved phoneme decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show for the first time that μECoG can enable high-quality speech decoding, demonstrating its ability to improve neural interfaces for neural speech prostheses.
Multivariate optimization of k for k-nearest-neighbor feature selection with dichotomous outcomes: complex associations, class imbalance, and application to RNA-Seq in Major Depressive Disorder
Authors: Dawkins Bryan A. , McKinney Brett A.
Published: May 2022

Optimization of nearest-neighbor feature selection depends on the number of samples and features, the type of statistical effect, the feature scoring algorithm, and class imbalance. We recently reported a fixed-k for Nearest-neighbor Projected-Distance Regression (NPDR) that addresses each of these parameters, except for class imbalance. To remedy this, we parameterize our NPDR fixed-k by the minority class size (minority-class-k). We also introduce a class-adaptive fixed-k (hit-miss-k) to improve performance of Relief-based algorithms on imbalanced data. In addition, we present two optimization methods, including constrained variable-wise optimized k (VWOK) and a fixed-k derived with principal components analysis (kPCA), both of which are adaptive to class imbalance. Using simulated data, we show that our methods significantly improve feature detection across a variety of nearest-neighbor feature scoring metrics, and we demonstrate superior performance in comparison to random forest and ridge regression using consensus-nested cross-validation (cnCV) for feature selection. We applied cnCV to RNASeq expression data from a study of Major Depressive Disorder (MDD) using NPDR with minority-class-k, random forest, and cnCV-ridge regression for gene importance. Pathway analysis showed that NPDR with minority-class-k alone detected genes with clear relevance to MDD, suggesting that our new fixed-k formula is an effective rule-of-thumb.
Semi-field and surveillance data define the natural diapause timeline forCulex pipiensacross the United States
Authors: Field Eleanor N. , Shepard John J. , Clifton Mark E. , Price Keith J. , Witmier Bryn J. , Johnson Kirk , Boze Broox , Abadam Charles , Ebel Gregory D. , Armstrong Philip M. , Barker Christopher M. , Smith Ryan C.
Published: May 2022

Culex pipiensis a globally-distributed mosquito of medical and veterinary importance, serving as a primary vector of West Nile virus (WNV). To survive winter, femaleCx. pipiensmosquitoes undergo adult reproductive diapause initiated by photoperiod and temperature cues. While well-studied under laboratory conditions, the environmental signals that promoteCx. pipiensdiapause induction in natural settings are less understood. Here, we evaluateCx. pipiensin laboratory and semi-field studies to examine diapause induction, defining an approximate timeline beginning in late-August where mosquitoes become receptive to diapause. Using gravid (reproductive) mosquito surveillance data as a proxy for adult diapause incidence for locations across the United States (California, Colorado, Connecticut, Illinois, Iowa, Minnesota, Pennsylvania, and Virginia), we demonstrate consistent population declines coinciding with periods of diapause receptivity except in hybridization zones whereCx. quinquefasciatusis present, suggesting thatCulexpopulation genetics can significantly impact end-season population trends. Together, this study defines a window for diapause induction across the United States, shaped by temperature, latitude, elevation, and mosquito population genetics. Coinciding with the cessation of WNV activity, these data can have important implications for mosquito control, where targeted efforts prior to diapause induction can decrease mosquito populations and WNV overwintering to reduce mosquito-borne disease incidence the following season.
Predictive Sequence Learning in the Hippocampal Formation
Authors: Chen Yusi , Zhang Huanqiu , Cameron Mia , Sejnowski Terrrence
Published: May 2022

The hippocampus receives sequences of sensory inputs from the cortex during exploration and encodes the sequences with millisecond precision. We developed a predictive autoencoder model of the hippocampus including the trisynaptic and monosynaptic circuits from the entorhinal cortex (EC). CA3 was trained as a self-supervised recurrent neural network to predict its next input. We confirmed that CA3 is prediction ahead by analyzing the spike coupling between simultaneously recorded neurons in the dentate gyrus, CA3 and CA1 of the mouse hippocampus. In the model, CA1 neurons signal prediction errors by comparing the prediction from CA3 to the next input directly from the EC. The model exhibits the rapid appearance and the slow fading of CA1 place cells, and displays replay and phase precession from CA3. The model could be learnt in a biologically plausible way with the help of error-encoding neurons. Similarities between the circuits in the hippocampus and thalamocortical circuits suggest that such computation motif could also underlie self-supervised sequence learning in the cortex.
The limitations of phenotype prediction in metabolism
Authors: Yubero Pablo , Lavin Alvar A. , Poyatos Juan F.
Published: May 2022

Phenotype prediction is at the core of many questions in biology. Prediction is frequently attained by determining statistical associations between genetic and phenotypic variation, ignoring the exact processes causing the phenotype. Here, we present a framework based on genome-scale metabolic reconstructions to reveal the mechanisms behind the associations. We compute a polygenic score (PGS) that identifies a set of enzymes as predictors of growth, the phenotype. This set arises from the synergy of the functional mode of metabolism in a particular environment and its evolutionary history, and is transportable to infer the phenotype across a range of environments. We also find that there exists an optimal genetic variation for predictability and demonstrate how the linear PGS can yet explain phenotypes generated by the underlying nonlinear biochemistry. Thus, the explicit model interprets the black-box statistical associations of the genotype-to-phenotype map and helps uncover what limits prediction in metabolism.