bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectroscopic and QM/MM studies of the Cu(I) binding site of the plant ethylene receptor ETR1
Authors: Cutsail George , Schott-Verdugo Stephan , Müller Lena , DeBeer Serena , Groth Georg , Gohlke Holger
Published: June 2022

Herein, we present the first spectroscopic characterization of the Cu(I) active site of the plant ethylene receptor ETR1. The X-ray absorption (XAS) and extended X-ray absorption fine structure (EXAFS) spectroscopy presented here establish that ETR1 has a low-coordinate Cu(I) site. The EXAFS resolves a mixed first coordination sphere of N/O and S scatterers at distances consistent with potential histidine and cysteine residues. This finding agrees with the coordination of residues C65 and H69 to the Cu(I) site, which are critical for ethylene activity and well-conserved. Further, the Cu K-edge XAS and EXAFS of ETR1 exhibit spectroscopic changes upon addition of ethylene that are attributed to modifications in the Cu(I) coordination environment, suggestive of ethylene binding. Results from umbrella sampling simulations of the proposed ethylene binding helix of ETR1 at a mixed quantum mechanics/molecular mechanics (QM/MM) level agree with the EXAFS fit distance changes upon ethylene binding, particularly in the increase of the distance between H69 and Cu(I), and yield binding energetics comparable to experimental dissociation constants. The observed changes in the copper coordination environment might be the triggering signal for the transmission of the ethylene response.
Impact of COVID-19 on College Students’ at One of the Most Diverse Campuses in the United States: A Factor Analysis of Survey Data
Authors: Liu Bowen , Huynh Edward , Li Chengcheng , Wu Qing
Published: June 2022

Objective

This survey study is designed to understand the impact of the COVID-19 pandemic on stress among specific sub-populations of college students.

Design, Settings and Participants

An online questionnaire was sent to the students from University of Nevada, Las Vegas between 2020 October and December to assess the psychological impact of COVID-19. A total of 2,091 respondents signed the consent form online and their responses were collected.

Methods

The Perceived Stress levels of college students were analyzed via exploratory factor analysis of a survey of college students, which was collected at the University of Nevada, Las Vegas (UNLV). An explanatory factor analysis was carried out on the Perceived Stress Scale (PSS-10) results. We subsequently analyzed each factor using stepwise linear regression that focused on various socio-demographic groups.

Results

A two-factor model was obtained using the explanatory factor analysis. After comparing with the past studies that investigated the factor structure of the PSS-10 scale, we identified these two factors as “Anxiety” and “Irritability”. The subsequent stepwise linear regression analysis suggested that gender and age (P< 0.01) are significantly associated with both factors. However, the ethnicities of students are not significantly associated with both factors.

Conclusions

To our knowledge, this is the first study that assessed the perceived stress of university students in the US during the COVID-19 pandemic. We showed that the PSS-10 scale could be summarized as a two-factor structure through an exploratory factor analysis. A stepwise regression approach was used and we found both of the factors are significantly associated with the gender of the participants. However, we found no significant association between both factors and ethnicity. In summary, our findings will help identify students with higher risk for stress and mental health issues in pandemics and future crises.

Strengths and limitations of this study

➣

To our knowledge, this is the first study that assessed the perceived stress of university students with PSS-10 scale in the US during the COVID-19 pandemic.

➣

Ethnicities of the participants are not significantly associated with the perceived stress. This finding is different compared to most of the previous studies.

➣

Only quantitative questions were used in this survey study. To gain a better understanding for the psychological impact of COVID-19 on students, qualitative questions need to be included in the future survey studies.

➣

The fact that only the participants who completed the PSS-10 scale were included in the quantitative analysis in this study leads to potential selection bias.

➣

The proportions of African American students and Pacific Islander students are low within the survey sample compared to the demographics of UNLV. This leads to potential volunteer bias.
Rapid compensatory evolution by secondary perturbation of a primary disrupted transcriptional network
Authors: Hsu Po-Chen , Cheng Yu-Hsuan , Liao Chia-Wei , Jhou Yu-Ting , Opoc Florica Jean Ganaden , Amine Ahmed A A , Leu Jun-Yi
Published: June 2022

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection over long time-scales, especially when a regulon is being transferred from one transcription factor (TF) to another. Cooperative DNA binding between redundant regulatory components at the intermediate transition stage is believed to mediate this process, enabling a conflict-free switch between two TFs without a disruptive change in gene expression. Here, we have performed an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant by means of a suppressor development strategy. Complete loss of SEF1 forced cells to activate a rewiring process to compensate for the pleiotropic defects arising from misexpression of multiple TCA cycle genes. Using different selective conditions, we identified one generalist and one specialist suppressive loss-of-function mutation of IRA1 and AZF1, respectively. Our subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1-PKA pathway. Azf1 loss-of-function triggers extensive gene expression changes responsible for both the compensatory and trade-off phenotypes. Our results indicate that the pleiotropic effects of dual perturbation of transcriptional networks are a potential mechanism for rapid adaptive compensation, facilitating the process of incipient transcriptional rewiring, and formation of complex traits.
The fat body cortical actin network regulatesDrosophilainter-organ nutrient trafficking, signaling, and adipose cell size
Authors: Ugrankar-Banerjee Rupali , Tran Son , Bowerman Jade , Kovalenko Anastasiia , Paul Blessy , Mike Henne W.
Published: June 2022

Defective nutrient storage and adipocyte enlargement (hypertrophy) are emerging features of metabolic syndrome and type 2 diabetes. Within adipose tissues, how the cytoskeletal network contributes to adipose cell size, nutrient uptake, fat storage, and signaling remain poorly understood. Utilizing theDrosophilalarval fat body (FB) as a model adipose tissue, we show that a specific actin isoform—Act5C—forms the cortical actin network necessary to expand adipocyte cell size for biomass storage in development. Additionally, we uncover a non-canonical role for the cortical actin cytoskeleton in inter-organ lipid trafficking. We find Act5C localizes to the FB cell surface and cell-cell boundaries, where it intimately contacts peripheral LDs (pLDs), forming a cortical actin network for cell architectural support. FB-specific loss of Act5C perturbs FB triglyceride (TG) storage and LD morphology, resulting in developmentally delayed larvae that fail to develop into flies. Utilizing temporal RNAi-depletion approaches, we reveal that Act5C is indispensable post-embryogenesis during larval feeding as FB cells expand and store fat. Act5C-deficient FBs fail to grow, leading to lipodystrophic larvae unable to accrue sufficient biomass for complete metamorphosis. In line with this, Act5C-deficient larvae display blunted insulin signaling and reduced feeding. Mechanistically, we also show this diminished signaling correlates with decreased lipophorin (Lpp) lipoprotein-mediated lipid trafficking, and find Act5C is required for Lpp secretion from the FB for lipid transport. Collectively, we propose that the Act5C-dependent cortical actin network ofDrosophilaadipose tissue is required for adipose tissue size-expansion and organismal energy homeostasis in development, and plays an essential role in inter-organ nutrient transport and signaling.
Effect of phone text message reminders on compliance with rabies post-exposure prophylaxis following dog-bites in rural Kenya
Authors: Chuchu Veronicah Mbaire , Nyamai Mutono , Bichanga Philet , Philip Kitala , Ksee Daniel , Muturi Mathew , Mwatondo Athman , Nasimiyu Caroline , Akunga Lawrence , Amiche Amine , Hampson Katie , Thumbi SM
Published: June 2022

Context

Prompt administration of post exposure prophylaxis (PEP) is one of the key strategies for ending human deaths from rabies. Delay in seeking first dose of rabies PEP or failure to complete the recommended PEP dosage may result in clinical rabies and death.

Objectives

To assess the efficacy of short message system (SMS) phone texts on adherence to scheduled PEP doses among bite patients in rural eastern Kenya.

Trial design and methods

We conducted a single arm before-after field trial that compared adherence among bite patients presenting at Makueni Referral Hospital in October – December 2018 (control group) and January – March 2019 (intervention group that received an SMS reminder one day prior to their scheduled PEP doses). Data on demographics, socio-economic status, circumstances surrounding the bite, expenditures related to the bite were collected for all patients.

Results

A total of 186 bite patients were enrolled in the study, with 82 (44%) being in the intervention and 104 (56%) in the control group. The odds of PEP completion was three times (OR 3.37, 95% CI 1.28, 10.20) among patients that received the SMS reminder compared to those that did not. The intervention group had better compliance on the scheduled doses 2 to 5 with a mean deviation of 0.18 days compared to 0.79 days for the control group (p = 0.004). The main reasons for non-compliance included lack of funds (30%), forgetfulness (23%) on days for follow-up treatment, among others. Although the majority of bite patients (94%) were under the Makueni medical insurance cover and did not pay for PEP, nearly all (96%, n=179) the bite patients incurred indirect costs of transport at an average of 4 USD (0 - 45 USD) per visit.

Conclusion

This study suggests integrating SMS reminders in healthcare service delivery increases compliance to PEP and may strengthen rabies control and elimination strategies.

Trial registration

The study trial is registered at US National Institute of Health (clinicalTrial.gov) identifier number NCT05350735. https://clinicaltrials.gov/ct2/show/NCT05350735
Electrostatic features for the Receptor binding domain of SARS-COV-2 wildtype and its variants. Compass to the severity of the future variants with the charge-rule
Authors: Barroso da Silva Fernando L. , Giron Carolina Corrêa , Laaksonen Aatto
Published: June 2022

Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pKas for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This “RBD charge rule” should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.

Categories and Subject Descriptors:
Exome sequencing identifies novel susceptibility genes and defines the contribution of coding variants to breast cancer risk
Authors: Wilcox Naomi , Dumont Martine , González-Neira Anna , Carvalho Sara , Beauparlant Charles Joly , Crotti Marco , Luccarini Craig , Soucy Penny , Dubois Stéphane , Nuñez-Torres Rocio , Pita Guillermo , Alonso M. Rosario , Álvarez Nuria , Baynes Caroline , Becher Heiko , Behrens Sabine , Bolla Manjeet K. , Castelao Jose E. , Chang-Claude Jenny , Cornelissen Sten , Dennis Joe , Dörk Thilo , Engel Christoph , Gago-Dominguez Manuela , Guénel Pascal , Hadjisavvas Andreas , Hahnen Eric , Hartman Mikael , Herráez Belén ,   SGBCC Investigators, Jung Audrey , Keeman Renske , Kiechle Marion , Li Jingmei , Loizidou Maria A. , Lush Michael , Michailidou Kyriaki , Panayiotidis Mihalis I. , Sim Xueling , Teo Soo Hwang , Tyrer Jonathan P. , van der Kolk Lizet E. , Wahlström Cecilia , Wang Qin , Benitez Javier , Schmidt Marjanka K. , Schmutzler Rita K. , Pharoah Paul D.P. , Droit Arnaud , Dunning Alison M. , Kvist Anders , Devilee Peter , Easton Douglas F. , Simard Jacques
Published: June 2022

Introductory paragraph

Linkage and candidate gene studies have identified several breast cancer susceptibility genes, but the overall contribution of coding variation to breast cancer is unclear. To evaluate the role of rare coding variants more comprehensively, we performed a meta-analysis across three large whole-exome sequencing datasets, containing 16,498 cases and 182,142 controls. Burden tests were performed for protein-truncating and rare missense variants in 16,562 and 18,681 genes respectively. Associations between protein-truncating variants and breast cancer were identified for 7 genes at exome-wide significance (P<2.5×10-6): the five known susceptibility genes BRCA1, BRCA2, CHEK2, PALB2 and ATM, together with novel associations for ATRIP and MAP3K1. Predicted deleterious rare missense or protein-truncating variants were additionally associated at P<2.5×10-6 for SAMHD1. The overall contribution of coding variants in genes beyond the previously known genes is estimated to be small.
Trends in severe acute malnutrition admissions, characteristics, and treatment outcomes in Malawi from 2011 through 2019
Authors: Daniel Allison I. , Kathumba Sylvester , Mitambo Collins , Chasweka Dennis , Voskuijl Wieger , Kamanga Esther , Mbale Emmie , Bandsma Robert H.J. , Potani Isabel
Published: June 2022

Background

Community-based Management of Acute Malnutrition (CMAM) has been successfully implemented across Malawi, yet trends in admissions, characteristics, and treatment outcomes in children with severe acute malnutrition (SAM) have not been examined. The objective was therefore to investigate trends in admissions, characteristics including percentage of children with SAM with HIV and oedema, and treatment outcomes across the decade following implementation of CMAM.

Methods

This research involved a retrospective analysis of existing data routinely collected across Malawi by the Ministry of Health between 2011 and 2019.

Results

These data showed an increase in outpatient therapeutic feeding (OTP) admissions from 30323 children in 2011 to 37655 in 2019 (p=0.045). However, a significant decrease in nutritional rehabilitation unit (NRU) admissions was observed, from 11389 annual admissions in 2011 to 6271 in 2019 (p=0.006). In children identified with SAM, the percentage with oedema decreased in OTPs with an average annual rate of reduction (AARR) of 5.6% (p=0.001) and by 26.2% in NRUs in this timeframe with an AARR of 8.5% (p<0.001). There was a decrease in the percentage of children with SAM who had HIV over time in OTPs with an AARR of 16.1% (p=0.001). HIV rates also decreased in NRUs with an AARR of 7.2% (p=0.4), but this difference was not significant. Death rates decreased in OTPs with an AARR of 6.0% (p=0.01). Mortality rates did not change in NRUs over time with an AARR of 0.9% (p=0.5) with the NRU mortality rate in 2019 being 11.0%.

Conclusions

These trends indicate that there has been an increase in OTP admissions and a corresponding decrease in NRU admissions. There have been decreases in the percentage of children with oedematous SAM in OTPs and in NRUs and with HIV in OTPs. Children remain at high risk of mortality in NRUs.

Competing interests

none to declare
Change in Effectiveness of Sotrovimab for Preventing Hospitalization and Mortality in COVID-19 Outpatients During the Omicron Phase
Authors: Aggarwal Neil R. , Beaty Laurel E. , Bennett Tellen D. , Carlson Nichole E. , Ginde Adit A.
Published: June 2022

Background

Sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic COVID-19 patients, was effective in preventing the progression of severe disease and mortality following SARS-CoV-2 Delta variant infection. It is not known whether sotrovimab is similarly effective for SARS-CoV-2 Omicron variant infection.

Methods

Observational cohort study of non-hospitalized adult patients with SARS-CoV-2 infection from December 26, 2021 to March 10, 2022 (>96% Omicron BA.1 variant), using electronic health records from a statewide health system linked to state-level vaccine and mortality data. We used propensity matching to select up to 3 patients not receiving mAbs or other authorized antivirals for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality. To evaluate change in sotrovimab effectiveness during the Omicron phase, we propensity matched sotrovimab-treated patients from Omicron to Delta (October 1-December 11, 2021) phases to each other and then to untreated controls with a treatment-variant interaction added to the logistic regression model.

Results

Of 30,247 patients with SARS-CoV-2 infection, we matched 1,542 receiving sotrovimab to 3,663 not receiving treatment. Compared to untreated patients, sotrovimab treatment was not associated with reduced odds of all-cause 28-day hospitalization (raw rate 2.5% versus 3.2%; adjusted OR 0.82, 95% CI 0.55, 1.19) or mortality (raw rate 0.1% versus 0.2%; adjusted OR 0.62, 95% CI 0.07, 2.78). In the combined analysis across Omicron and Delta phases, the observed treatment OR was higher during Omicron than during Delta (OR 0.85 vs. 0.39, respectively; interaction p=0.053)

Conclusion

Real-world evidence demonstrated sotrovimab was not associated with reduced hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Omicron BA.1 phase and attenuated compared to the Delta phase

Real-world evidence demonstrates that the neutralizing monoclonal antibody sotrovimab was not associated with lower 28-day hospitalization and mortality rates when administered to high-risk outpatients recently infected with SARS-CoV-2 during the Omicron variant phase, compared to a propensity-matched cohort of untreated outpatients.
How do Urban Factors Control the Severity of COVID-19?
Authors: Roxon Jacob , Dumont Marie-Sophie , Vilain Eric , Pellenq Roland J.M.
Published: June 2022

Human health in urban environment has emerged as a primary focus of sustainable development during the time of global pandemic caused by a severe acute respiratory syndrome due to the SARS-CoV-2 coronavirus, COVID-19. It has reshaped the world with the way our communities interact, people work, commute, and spend their leisure time. While different mitigation solutions for controlling COVID-19 virus transmission have already been established, global models that would explain and predict the impact of urban environments on the case fatality ratio CFR of COVID-19 (defined as the number of deaths divided by the number of cases over a time window) are missing. Here, with readily available data from public sources, we study the CFR of the coronavirus for 118 locations (city zip-codes, city boroughs, and cities) worldwide to identify the links between the CFR and outdoor, indoor and personal urban factors. We show that a probabilistic model, optimized on the sample of 20 districts from 4 major US cities, provides an accurate predictive tool for the CFR of COVID-19 regardless of the geographical location. When adjusted for the population, our model can be used to evaluate risk and severity of the disease at multi-geospatial scales worldwide ranging from zip-codes and neighborhoods to cities and countries for different waves of the pandemic. Our results suggest that although disease screening and vaccination policies to containment and lockdowns remain critical in controlling the spread of airborne diseases, urban factors such as population density, humidity, or order of buildings, should all be taken into consideration when identifying resources and planning targeted responses to mitigate the impact and severity of the viruses transmitted through air. We advocate the study of urban factors as a path towards facilitating timely deployment of targeted countermeasures and confinement strategies where sharing of personal information and availability of tests may be restricted or limited.
RNA-Seq-Pop: Exploiting the sequence in RNA-Seq - a Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae
Authors: Nagi Sanjay C , Oruni Ambrose , Weetman David , Donnelly Martin J
Published: June 2022

Background

We provide a reproducible and scalable Snakemake workflow, called RNA-Seq-Pop, which provides end-to- end analysis of RNA-Seq data sets. The workflow allows the user to perform quality control, differential expression analyses, call genomic variants and generate a range of summary statistics. Additional options include the calculation of allele frequencies of variants of interest, summaries of genetic variation and population structure (in measures such as nucleotide diversity, Watterson’s θ, and PCA), and genome wide selection scans (Fst, PBS), together with clear visualisations. We demonstrate the utility of the workflow by investigating pyrethroid-resistance in selected strains of the major malaria mosquito, Anopheles gambiae. The workflow provides additional modules specifically for An. gambiae, including estimating recent ancestry and determining the karyotype of common chromosomal inversions.

Results

The Busia lab-colony used for selections was collected in Busia, Uganda, in November 2018. We performed a comparative analysis of three groups: a parental G24 Busia strain; its deltamethrin-selected G28 offspring; and the susceptible reference strain Kisumu. Measures of genetic diversity reveal patterns consistent with that of laboratory colonisation and selection, with the parental Busia strain exhibiting the highest nucleotide diversity of 1.04·10-3, followed by the selected Busia offspring (7.1·10-4), and finally, Kisumu (6.2·10-4). Differential expression and variant analyses reveal that the selected Busia colony exhibits a number of distinct mechanisms of pyrethroid resistance, including the Vgsc-995S target-site mutation, upregulation of SAP genes, P450s, and a cluster of carboxylesterases. During deltamethrin selections, the 2La chromosomal inversion rose in frequency (from 33% to 86%), suggesting a link with pyrethroid resistance, which was previously observed in field samples from the same region. RNA-Seq-Pop analysis also reveals that the most widely-used insecticide-susceptible An. gambiae strain, Kisumu, appears to be a hybrid strain of An. gambiae and its sibling species An. coluzzii, which should be taken into consideration in future research.

RNA-Seq-Pop is designed for ease of use, does not require programming skills and integrates the package manager Conda to ensure that all dependencies are automatically installed for the user. We anticipate that the workflow will provide a useful tool to facilitate reproducible, transcriptomic studies in An. gambiae and other taxa.
Machine learning-based classification of binary dynamic fluorescence signals reveals muscle stem cell fate transitions in response to pro-regenerative niche factors
Authors: Togninalli Matteo , Ho Andrew T.V. , Madl Christopher M. , Holbrook Colin A. , Wang Yu Xin , Magnusson Klas E.G. , Kirillova Anna , Chang Andrew , Blau Helen M.
Published: June 2022

The proper regulation of muscle stem cell (MuSC) fate by cues from the niche is essential for regeneration of skeletal muscle. How pro-regenerative niche factors control the dynamics of MuSC fate decisions remains unknown due to limitations of population-level endpoint assays. To address this knowledge gap, we developed a novel binary dynamic fluorescence time lapse imaging analysis (BDFA) approach that leverages machine learning classification strategies to track single cell fate decisions with high temporal resolution. Using two fluorescent reporters that read out maintenance of stemness and myogenic commitment, we constructed detailed lineage trees for individual MuSCs and their progeny, classifying each division event as symmetric self-renewing, asymmetric, or symmetric committed. Our analysis reveals that treatment with the lipid metabolite, prostaglandin E2 (PGE2), accelerates the rate of MuSC proliferation over time, while biasing division events toward symmetric self-renewal. In contrast, the IL6 family member, Oncostatin M (OSM) decreases the proliferation rate after the first generation, while blocking myogenic commitment. These insights into the dynamics of MuSC regulation by niche cues were uniquely enabled by our BDFA approach. We anticipate that similar binary live cell readouts derived from BDFA will markedly expand our understanding of how niche factors control tissue regeneration in real time.
A beary good genome: Haplotype-resolved, chromosome-level assembly of the brown bear (Ursus arctos)
Authors: Armstrong Ellie E. , Perry Blair W. , Huang Yongqing , Garimella Kiran V. , Jansen Heiko T. , Robbins Charles T. , Tucker Nathan R. , Kelley Joanna L.
Published: June 2022

The brown bear (Ursus arctos) is the second largest and most widespread extant terrestrial carnivore on Earth and has recently emerged as a medical model for human metabolic diseases. Here, we report a fully-phased chromosome-level assembly of a male North American brown bear built by combining Pacific Biosciences (PacBio) HiFi data and publicly available Hi-C data. The final genome size is 2.47 Gigabases (Gb) with a scaffold and contig N50 length of 70.08 and 43.94 Mb, respectively. BUSCO analysis revealed that 94.5% of single-copy orthologs from mammalia were present in the genome (the highest of any ursid genome to date). Repetitive elements accounted for 44.48% of the genome and a total of 20,480 protein coding genes were identified. Based on whole genome alignment, the brown bear is highly syntenic with the polar bear, and our phylogenetic analysis of 7,246 single-copy BUSCOs supports the currently proposed species tree for Ursidae. This highly contiguous genome assembly will support future research on both the evolutionary history of the bear family and the physiological mechanisms behind hibernation, the latter of which has broad medical implications.

Significance

Brown bears (Ursus arctos) are the most widespread, large terrestrial carnivore on the planet and represent an interesting example of speciation through hybridization, as well as a medical model for sedentary lifestyle-related disease. Although a previous genome for a brown bear has been published, the reported contig N50 was low (only ∼530 kb), despite being scaffolded into putative chromosomes. Genomes of this quality limit the accuracy of analyses which rely on long contiguous stretches of the genome to be assembled (such as with many demographic analyses) as well as attempts at connecting genotype to phenotype (such as in association analyses). In order to support studies on both the complex hybridization history of the brown bear and investigations into medically-relevant phenotypes, we generated a fully-phased, chromosome-level assembly from a male grizzly bear. The genome has a total size of 2.47 Gb and 90% of the genome is contained in 36 scaffolds, roughly corresponding to one autosome per scaffold. This high-quality genome will enable studies across a variety of disciplines, including conservation, evolution, and medicine.
Rapid, scalable, combinatorial genome engineering by Marker-less Enrichment and Recombination of Genetically Engineered loci (MERGE)
Authors: Abdullah Mudabir , Greco Brittany M. , Laurent Jon M. , Vandeloo Michelle , Marcotte Edward M. , Kachroo Aashiq H.
Published: June 2022

Large-scale genome engineering in yeast is feasible primarily due to prodigious homology-directed DNA repair (HDR), a plethora of genetic tools, and simple conversion between haploid and diploid forms. However, a major challenge to rationally building multi-gene processes in yeast arises due to the combinatorics of combining all of the individual edits into the same strain. Here, we present an approach for scalable, precise, multi-site genome editing that combines all edits into a single strain without the need for selection markers by using CRISPR-Cas9 and gene drives. First, we show that engineered loci become resistant to the corresponding CRISPR reagent, allowing the enrichment of distinct genotypes. Next, we demonstrate a highly efficient gene drive that selectively eliminates specific loci by integrating CRISPR-Cas9 mediated Double-Strand Break (DSB) generation and homology-directed recombination with yeast sexual assortment. The method enables Marker-less Enrichment and Recombination of Genetically Engineered loci (MERGE) in yeast. We show that MERGE converts single heterologous yeast loci to homozygous loci at ∼100% efficiency, independent of chromosomal location. Furthermore, MERGE is equally efficient at converting and combining loci, thus identifying viable intermediate genotypes. Finally, we establish the feasibility of MERGE by engineering a fungal carotenoid biosynthesis pathway and most of the human α proteasome core into yeast. MERGE, therefore, lays the foundation for marker-less, highly efficient, and scalable combinatorial genome editing in yeast.
Discovery of a broadly-neutralizing human antibody that can rescue mice challenged with neurotoxin-rich snake venoms
Authors: Ledsgaard Line , Wade Jack , Boddum Kim , Oganesyan Irina , Harrison Julian , Jenkins Timothy P. , Villar Pedro , Leah Rachael A. , Zenobi Renato , McCafferty John , Lomonte Bruno , Gutiérrez José M. , Laustsen Andreas H. , Karatt-Vellatt Aneesh
Published: June 2022

Snakebite envenoming continues to claim many lives across the globe, necessitating the development of improved therapies. To this end, human monoclonal antibodies may possess advantages over current plasma-derived antivenoms by offering superior safety and improved neutralization capacity. However, as new antivenom products may need to be polyvalent, i.e., target multiple different snake species, without dramatically increasing dose or cost of manufacture, such monoclonal antibodies need to be broadly-neutralizing. Here, we report the establishment of a pipeline for the discovery of high affinity broadly-neutralizing human monoclonal antibodies. We further demonstrate its utility by discovering an antibody that can prevent lethality induced by N. kaouthia whole venom at an unprecedented low molar ratio of one antibody per toxin, and which also prolongs survival of mice injected with Dendroaspis polylepis or Ophiophagus hannah whole venoms.
ReachingBot: an automated and scalable benchtop device for highly parallel Single Pellet Reach-and-Grasp training and assessment in mice
Authors: Kakanos Sotiris G. , Gadiagellan Dhireshan , Kim Eugene , Cash Diana , Moon Lawrence D. F.
Published: June 2022

The single pellet reaching and grasp (SPRG) task is a behavioural assay widely used to study motor learning, control and recovery after nervous system injury in animals. The manual training and assessment of the SPRG is labour intensive and time consuming and has led to the development of multiple devices which automate the SPRG task. Current state-of-the-art desktop methods either still require attendance, manual classification of trial outcome, or expensive locally-installed hardware such as graphical processing units (GPUs). Here, using robotics, computer vision, and machine learning analysis of videos, we describe a novel cost-effective benchtop device that can be left unattended, presents pellets to mice automatically, video records each trial, and, using two supervised learning algorithms, classifies the outcome of each trial automatically with an accuracy of greater than 94% without the use of GPUs. Finally, the device is simple in design with few components meaning manufacturing at scale is straightforward and, with few moving parts, reliable and robust. Our devices can also be operated using our cross-platform Graphical User Interface (GUI), meaning no knowledge of programming is required by its users.

We show that these devices can train 30 mice with them collectively performing ~83,000 trials over 3 months, saving users an estimated 8 and half hours of labour per day. Over five weeks, most mice undertook more trials per session and retrieved more pellets successfully. 21 out of 30 mice retrieved at least 40% of pellets successfully in at least one session during the training period. Devices measured motor deficits induced in mice by a focal ischaemic stroke; some mice showed large persistent deficits whilst others showed only transient deficits. This highlights the heterogeneity in reaching outcomes following stroke. We conjecture that reach-and-grasp is represented in motor cortex bilaterally but with greater asymmetry in some mice than in others. We predict that bilateral lesions of motor cortex would cause long-lasting deficits in reach-and-grasp in mice.

We propose a strategy for preclinical evaluation of novel therapeutics that improve reach-and-grasp by pre-screening a large cohort of mice automatically and excluding those that fail to achieve pre-specific success rates, which generates a cohort of mice trained with consistent performance levels, suitable for randomization to treatment arms in a preclinical study. Well-powered sample sizes are easily achievable. Highly parallel automated training and assessment should accelerate the development of new therapies for movement disorders.
Identification of essential modules regulating T cell migration to the central nervous system in multiple sclerosis
Authors: Kendirli Arek , de la Rosa Clara , Lämmle Katrin F. , Eglseer Klara , Bauer Isabel J. , Kavaka Vladyslav , Winklmeier Stephan , Wichmann Christian , Gerdes Lisa-Ann , Kümpfel Tania , Dornmair Klaus , Beltrán Eduardo , Kerschensteiner Martin , Kawakami Naoto
Published: June 2022

Multiple sclerosis (MS) is a neuroinflammatory disease initiated by the infiltration of autoreactive T cells into the central nervous system (CNS). Several molecules that modulate T cell CNS infiltration in MS have been identified, but how the components of cell adhesion, migration and signalling pathways interact to execute this fundamental step in MS pathogenesis is unknown. We conducted a genome-wide in vivo CRISPR screen in an experimental autoimmune encephalomyelitis model of MS and identified 18 essential facilitators of T cell migration that include known targets of MS therapies. Combining in vitro studies with in vivo cell transfer and multiphoton microscopy enabled us to reveal three functional modules, centred around the adhesion molecule α4-integrin, the chemokine receptor CXCR3, and the GRK2 kinase, that are required for the migration of autoreactive CD4+ T cells into the CNS. Single-cell analysis of T cells from patients with MS confirmed that the expression of the essential regulators correlates with the propensity of CD4+ T cells to reach the CNS. Taken together, our data reveal the identity and functions of key modules that govern the critical step in the induction of MS lesions.
Fidelity of and biases in the developmental acquisition of song tempo in a songbird
Authors: James Logan S. , Wang Angela S. , Sakata Jon T.
Published: June 2022

The temporal organization of sounds used in social contexts can provide information about signal function and evoke varying responses in listeners (receivers). For example, music is a universal and learned human behavior that is characterized by different rhythms and tempos that can evoke disparate responses in listeners. Similarly, birdsong is a ubiquitous social behavior in birds that is learned during critical periods in development and used to evoke physiological and behavioral responses in listeners. Recent investigations have begun to reveal the breadth of universal patterns in birdsong and their similarity to common patterns in speech and music, but relatively little is known about the degree to which biological predispositions and developmental experiences interact to shape the temporal patterning of birdsong. Here, we investigated how biological predispositions modulate the acquisition and production of an important temporal feature of birdsong, namely the duration of silent intervals (“gaps”) between vocal elements (“syllables”). Through analyses of semi-naturally raised and experimentally tutored zebra finches, we observed that juvenile zebra finches imitate the durations of the silent gaps in their tutor’s song with high fidelity and can “alter” the durations of gaps toward a central duration. When juveniles were experimentally tutored with stimuli containing a wide range of gap durations, we observed biases in the stereotypy but not in the central tendency of gap durations. Together, these studies demonstrate how biological predispositions and developmental experiences differently affect distinct temporal features of birdsong and highlight similarities in developmental plasticity across birdsong, speech, and music.
LinAliFold and CentroidLinAliFold: Fast RNA consensus secondary structure prediction for aligned sequences using beam search methods
Authors: Fukunaga Tsukasa , Hamada Michiaki
Published: June 2022

RNA consensus secondary structure prediction from aligned sequences is a powerful approach for improving the secondary structure prediction accuracy. However, because the computational complexities of conventional prediction tools scale with the cube of the alignment lengths, their application to long RNA sequences, such as viral RNAs or long non-coding RNAs, requires significant computational time. In this study, we developed LinAliFold and CentroidLinAliFold, fast RNA consensus secondary structure prediction tools based on minimum free energy and maximum expected accuracy principles, respectively. We achieved software acceleration using beam search methods that were successfully used for fast secondary structure prediction from a single RNA sequence. Benchmark analyses showed that LinAliFold and CentroidLinAliFold were much faster than the existing methods while preserving the prediction accuracy. As an empirical application, we predicted the consensus secondary structure of coronaviruses with approximately 30,000 nt in 5 and 76 minutes by LinAliFold and CentroidLinAliFold, respectively. We confirmed that the predicted consensus secondary structure of coronaviruses was consistent with the experimental results. The source code is freely available at https://github.com/fukunagatsu/LinAliFold-CentroidLinAliFold.
Promoting extinction or minimizing growth? The impact of treatment on trait trajectories in evolving populations
Authors: Raatz Michael , Traulsen Arne
Published: June 2022

When cancers or bacterial infections establish, small populations of cells have to free themselves from homoeostatic regulations that prevent their expansion. Trait evolution allows these populations to evade this regulation, escape stochastic extinction and climb up the fitness landscape. In this study, we analyse this complex process and investigate the fate of a cell population that underlies the basic processes of birth, death and mutation. We find that the shape of the fitness landscape dictates a circular adaptation trajectory in the trait space spanned by birth and death rates. We show that successful adaptation is less likely for parental populations with higher turnover (higher birth and death rates). Including density- or trait-affecting treatment we find that these treatment types change the adaptation dynamics in agreement with a geometrical analysis of fitness gradients. Treatment strategies that simultaneously target birth and death rates are most effective, but also increase evolvability. By mapping physiological adaptation pathways and molecular drug mechanisms to traits and treatments with clear eco-evolutionary consequences, we can achieve a much better understanding of the adaptation dynamics and the eco-evolutionary mechanisms at play in the dynamics of cancer and bacterial infections.
Stochastic competitive release and adaptive chemotherapy
Authors: Park J. , Newton P.K.
Published: June 2022

We develop a finite-cell model of tumor natural selection dynamics to investigate the stochastic fluctuations associated with multiple rounds of adaptive chemotherapy. The adaptive cycles are designed to avoid chemo-resistance in the tumor by managing the ecological mechanism ofcompetitive releaseof a resistant sub-population. Our model is based on a three-component evolutionary game played among healthy (H), sensitive (S), and resistant (R) populations ofNcells, with a chemotherapy control parameter,C(t), used to dynamically impose selection pressure on the sensitive sub-population to slow tumor growth but manage competitive release of the resistant population. The adaptive chemo-schedule is designed based on the deterministic (N→ ∞) adjusted replicator dynamical system, then implemented using the finite-cell stochastic frequency dependent Moran process model (N= 10K– 50K) to ascertain the size and variations of the stochastic fluctuations associated with the adaptive schedules. We quantify the stochastic fixation probability regions of theRandSpopulations in theHSRtri-linear phase plane as a function of the control parameterC∈ [0, 1], showing that the size of theRregion increases with increasingC. We then implement an adaptive time-dependent scheduleC(t) for the stochastic model and quantify the variances (using principal component coordinates) associated with the evolutionary cycles for multiple rounds of adaptive therapy, showing they grow according to power-law scaling. The simplified low-dimensional model provides some insights on how well multiple rounds of adaptive therapies are likely to perform over a range of tumor sizes if the goal is to maintain a sustained balance among competing sub-populations of cells so as to avoid chemo-resistance via competitive release in a stochastic environment.
Activity regulates a cell type-specific mitochondrial phenotype in zebrafish lateral line hair cells
Authors: McQuate Andrea , Knecht Sharmon , Raible David W.
Published: June 2022

Hair cells of the inner ear are particularly sensitive to changes in mitochondria, the subcellular organelles necessary for energy production in all eukaryotic cells. There are over thirty mitochondrial deafness genes, and mitochondria are implicated in hair cell death following noise exposure, aminoglycoside antibiotic exposure, as well as in age-related hearing loss. However, little is known about the basic aspects of hair cell mitochondrial biology. Using hair cells from the zebrafish lateral line as a model and serial block-face scanning electron microscopy, we have quantifiably characterized a unique hair cell mitochondrial phenotype that includes (1) a high mitochondrial volume, and (2) specific mitochondrial architecture: multiple small mitochondria apically, and a reticular mitochondrial network basally. This phenotype develops gradually over the lifetime of the hair cell. Disrupting this mitochondrial phenotype with a mutation in opa1 impacts mitochondrial health and function. While hair cell activity is not required for the high mitochondrial volume, it shapes the mitochondrial architecture, with mechanotransduction necessary for all patterning, and synaptic transmission necessary for development of mitochondrial networks. These results demonstrate the high degree to which hair cells regulate their mitochondria for optimal physiology, and provide new insights into mitochondrial deafness.
Optimized path planning surpasses human efficiency in cryo-EM imaging
Authors: Li Yilai , Fan Quanfu , Xu Ziping , Lee Emma Rose , Cohn John , Demers Veronique , Lee Ja Young , Yip Lucy , Cianfrocco Michael A. , Vos Seychelle M.
Published: June 2022

Cryo-electron microscopy (cryo-EM) represents a powerful technology for determining atomic models of biological macromolecules(Kühlbrandt, 2014). Despite this promise, human-guided cryo-EM data collection practices limit the impact of cryo-EM because of a path planning problem: cryo-EM datasets typically represent 2-5% of the total sample area. Here, we address this fundamental problem by formalizing cryo-EM data collection as a path planning optimization from low signal data. Within this framework, we incorporate reinforcement learning (RL) and deep regression to design an algorithm that uses distributed surveying of cryo-EM samples at low magnification to learn optimal cryo-EM data collection policies. Our algorithm - cryoRL - solves the problem of path planning on cryo-EM grids, allowing the algorithm to maximize data quality in a limited time without human intervention. A head-to-head comparison of cryoRL versus human subjects shows that cryoRL performs in the top 10% of test subjects, surpassing the majority of users in collecting high-quality images from the same sample. CryoRL establishes a general framework that will enable human-free cryo-EM data collection to increase the impact of cryo-EM across life sciences research.
O-GlcNAc transferase modulates formation of clathrin-coated pits
Authors: Rahmani Sadia , Ahmed Hafsa , Ibazebo Osemudiamen , Fussner-Dupas Eden , Wakarchuk Warren W. , Antonescu Costin N.
Published: June 2022

Clathrin-mediated endocytosis (CME) controls the internalization and function of a wide range of cell surface proteins. CME occurs by the assembly of clathrin and many other proteins on the inner leaflet of the plasma membrane into clathrin-coated pits (CCPs). These structures recruit specific membrane protein cargo destined for internalization and trigger the generation of membrane curvature that precedes eventual scission of CCPs from the plasma membrane to yield intracellular vesicles. The diversity of cell surface protein cargo thus controlled by CME indicates that CCP formation is regulated to allow cellular adaptation under different contexts. Of interest is how cues derived from cellular metabolism may regulate CME, given the reciprocal role of CME in controlling cellular metabolism. The modification of proteins with O-linked β-N-acetylglucosamine (O-GlcNAc) is sensitive to nutrient availability and may allow cellular adaptation to different metabolic conditions. We examined how the modification of proteins with O-GlcNAc may control CCP formation and thus CME. We used perturbation of key enzymes responsible for protein O-GlcNAc modification, as well as specific mutants of the endocytic regulator AAK1 predicted to be impaired for O-GlcNAc modification. We identify that CCP initiation and the assembly of clathrin and other proteins within CCPs is controlled by O-GlcNAc protein modification. This reveals a new dimension of regulation of CME and highlights the important reciprocal regulation of cellular metabolism and endocytosis.