bluuebunny/crossref_metadata_2025 huggingface dataset:
Streptomyces montanisoli sp. nov., exhibiting antimicrobial activity, isolated from mountain soil around a decaying tree
Authors: Lee Jae Ha , Jeong Ji Won , Lee Dong Hyeon , Kim Seung Bum
Published: April 2022

A Gram-stain-positive, aerobic actinobacterial strain designated MMS17-BM035T isolated from mountain soil around a decaying tree was subjected to taxonomic characterization. The isolate developed extensively branched substrate mycelia and white aerial hyphae on International

Streptomyces

Project 2 agar. Strain MMS17-BM035T grew at 15–34 °C (optimum, 30 °C), at pH 5.0–8.0 (optimum, pH 7.0) and in the presence of 0–6 % NaCl (optimum, 0 %). Analysis of 16S rRNA gene sequences indicated that MMS17-BM035T fell into a phylogenetic cluster belonging to the genus

Streptomyces

. MMS17-BM035T shared the highest sequence similarity of 99.45 % with

Streptomyces fuscigenes

JBL-20T, and no higher than 98.7 % with other species of

Streptomyces

. Based on the orthologous average nucleotide identity, MMS17-BM035T was again mostly related to

S. fuscigenes

JBL-20T with 84.14 % identity, and less than 80 % with other species. The digital DNA–DNA hybridization analysis also indicated low levels of relatedness with related species, as the highest value was observed with

S. fuscigenes

JBL-20T (28.8 %). The major fatty acids of the strain were anteiso-C15 : 0, a summed feature (consisting of C18 : 1 ω7c/C18 : 1 ω6c), iso-C15 : 0, C16 : 0 and C20 : 0. The major respiratory quinones were MK-9(H4) and MK-9(H6). The diagnostic polar lipids were diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylinositolmannoside. The major cell-wall diamino acid was ll-diaminopimelic acid, and the characteristic whole-cell sugars were glucose and ribose. The DNA G+C content was 72.1 mol%. Strain MMS17-BM035T exhibited antimicrobial activity against several Gram-positive bacteria and yeasts. Based on both phenotypic and phylogenetic evidences, strain MMS17-BM035T should be classified as representing a novel species, for which the name Streptomyces montanisoli sp. nov. (type strain=MMS17-BM035T=KCTC 49544T=JCM 34528T) is proposed.
Evaluation of antioxidant status and oxidative stress markers in HTLV-1 infected individuals: correlation with the severity of virus-induced complications
Authors: Yaghoubi Neda , Youssefi Masoud , Rafat Panah Hooshang , Jarahi Lida , Zahedi Avval Farnaz
Published: April 2022

Introduction. Human T-cell lymphotropic virus type 1 (HTLV-1), a well-known member of the retroviridae family, potentially causes serious outcomes including adult T-cell leukaemia/lymphoma (ATLL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM-TSP). Oxidative stress plays a key role in progression and clinical exacerbation of several chronic infections. We have previously shown a reduction in serum total antioxidant capacity (TAC) during HTLV-1 infection and this study was set out to investigate the reasons for TAC reduction.

Hypothesis/Gap Statement. Oxidant/antioxidant imbalance during HTLV-1 infection may result from disruptions in oxidant levels or antioxidant defence system.

Aim. This study aimed to analyse the key enzymes and oxidant molecules playing important roles in virus-induced oxidative stress.

Methodology. We measured serum activities of the major antioxidant enzymes; superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX) as well as serum concentrations of the main oxidant markers: nitric oxide (NO) and malondialdehyde (MDA). Totally 40 HTLV-1 infected patients and 40 healthy controls were enrolled in this study. The patient group consisted of chronic carriers and patients with HAM-TSP (N=20).

Results. The current study found that serum levels of MDA and NO were significantly higher in patient groups particularly in HAM-TSP patients (P<0.05). In addition, a reductive trend was observed in the serum activities of CAT, SOD, and GPX in HTLV-1 infected patients compared with healthy controls (P<0.05).

Conclusion. Reduced activities of CAT, SOD, and GPX antioxidant enzymes along with the observed elevated concentrations of oxidant molecules may contribute to oxidative stress and worse outcomes during HTLV-1 infection.
Clinical description, molecular delineation and genotype-phenotype correlation in 340 patients with KBG syndrome: Addition of 67 new patients
Authors: Martínez-Cayuelas Elena , Blanco-Kelly Fiona , López-Grondona Fermina , Tahsin-Swafiri Saoud , López-Rodríguez Rosario , Pozo Rebeca Losada-Del , Mahillo Ignacio , Moreno Beatriz , Rodrigo-Moreno María , Casas-Alba Dídac , López-González Aitor , García-Miñaur Sixto , de los Ángeles Mori María , Pacio-Mínguez Marta , Rikeros-Orozco Emi , Santos-Simarro Fernando , Cruz-Rojo Jaime , Quesada-Espinosa Juan Francisco , Teresa Sánchez-Calvin María , Pozo Jaime Sánchez-del , Bernadó-Fonz Raquel , Isidoro-García María , Ruiz-Ayucar Irene , Álvarez María Isabel , Blanco-Lago Raquel , De Azua-Brea Begoña , Eirís Jesús , García-Peñas Juan José , Gil- Fournier Belén , Gómez-Lado Carmen , Irazabal Nadia , López Vanessa , Madrigal Irene , Málaga Ignacio , Martínez-Menéndez Beatriz , Ramiro-Leon María Soraya , García-Hoyos María , Prieto-Matos Pablo , López-Pisón Javier , Aguilera-Albesa Sergio , de Andrés Sara Álvarez , Fernández-Jaén Alberto , Llano-Rivas Isabel , Gener Blanca , Ayuso Carmen , Arteche-López Ana , Palomares-Bralo María , Cueto Anna , Valenzuela Irene , Martínez-Monseny Antonio F. , Lorda-Sánchez Isabel , Almoguera Berta
Published: April 2022

Background

KBG syndrome is a highly variable neurodevelopmental disorder and clinical diagnostic criteria have changed as new patients have been published. Both loss-of-function sequence variants and large deletions (CNVs) involving ANKRD11 have been involved in KBG, but no genotype-phenotype correlation has been reported to date. This study presents the clinical and molecular characteristics of 67 new patients with KBG syndrome and the results of the first genotype-phenotype correlation leveraging data on 273 patients previously published.

Methods

67 patients with KBG syndrome were recruited through a Spanish collaborative effort and were assessed using a custom phenotypic questionnaire. The frequency of all features was calculated. Manifestations present in >50% of the patients and a “severity score” were used to perform a genotype-phenotype correlation in the 340 KBG patients.

Results

Neurodevelopmental delay (95%), comorbidites (82.8%), macrodontia (80.9%), triangular face (71%), characteristic ears (76%), nose (75.9%) and eyebrows (67.3%) were the most prevalent features in the 67 patients. The genotype-phenotype correlation yielded significant associations with the triangular face (71.1% in patients with sequence variants vs 45.2% in CNVs, p=0.015), short stature (62.5% variants in exon 9 vs. 27.8% outside; p=0.009) and macrodontia (with larger deletions, p=0.028), ID/ADHD/ASD (70.4% in c.1903_1907del vs. 89.4%; p=0.012) and a higher phenotypic score in patients with sequence variants compared with CNVs (p=0.005).

Conclusions

We present a detailed phenotypic description of KBG syndrome in the largest series of patients reported to date, provide evidence of a genotype-phenotype correlation between some KBG features and specific ANKRD11 aberrations, and propose updated clinical diagnostic criteria based on our findings.
High-resolution characterization of recent tuberculosis transmission in Botswana using geospatial and genomic data – the Kopanyo Study
Authors: Baker Chelsea R. , Barilar Ivan , de Araujo Leonardo S. , Rimoin Anne W. , Parker Daniel M. , Boyd Rosanna , Tobias James L. , Moonan Patrick K. , Click Eleanor S. , Finlay Alyssa , Oeltmann John E. , Minin Vladimir N. , Modongo Chawangwa , Zetola Nicola M. , Niemann Stefan , Shin Sanghyuk S.
Published: April 2022

Introduction

Combining genomic and geospatial data can be useful for understandingMycobacterium tuberculosis(Mtb) transmission in high tuberculosis burden settings.

Methods

We performed whole genome sequencing (WGS) on Mtb DNA extracted from sputum cultures from a population-based tuberculosis study conducted in 2012–2016 in Gaborone, Botswana. We used kernel density estimation, spatialK-functions, and created spatial distributions of phylogenetic trees. WGS-based clusters of isolates ≤5 single nucleotide polymorphisms were considered recent transmission, and large WGS-based clusters (≥10 members) were considered outbreaks.

Results

We analyzed data from 1449 participants with culture-confirmed TB. Among these, 946 (65%) participants had both molecular and geospatial data. A total of 62 belonged to five large outbreaks (10–19 participants each). Geospatial clustering was detected in two of the five large outbreaks, suggesting heterogeneous spatial patterns within the community.

Conclusions

Integration of genomic and geospatial data identified distinct patterns of tuberculosis transmission in a high-tuberculosis burden setting. Targeted interventions in these smaller geographies may interrupt on-going transmission.
The Dawn is Coming —— the Description and Prediction of Omicron SARSCoV-2 Epidemic Outbreak in Shanghai by Mathematical Modeling
Authors: Jiang Minghao , Meng Guoyu , Wu Geng
Published: April 2022

The COVID-19 Omicron outbreak in Shanghai has been going on for >1 month and 25 million population is subjected to strict lock-down quarantine. Until now, it is not clear how long this epidemic might end. Here, we present a time-delayed differentiation equation model to evaluate and forecast the spreading trend. Our model provides important parameters such as the average quarantine ratio, the detection interval from being infected to being tested positive, and the spreading coefficient to better understand the omicron progression. After data fitting, we concluded on 11 April that the maximum overall number infected in Shanghai would exceed 300,000 on 14 April and the turning point would be in the coming days around 13-15 April, 2022, which is perfectly in line with the real-life infection number. Furthermore, the quarantine ratio in Shanghai was found to be greater than 1, supportive of the effectiveness of the strict lockdown policy. Altogether, our mathematical model helps to define how COVID-19 epidemic progresses under the Shanghai lock-down unprecedented in human history and the Chinese zero tolerance policy.
Previous SARS-CoV-2 infection or a third dose of vaccine elicited cross-variant neutralizing antibodies in vaccinated solid organ transplant recipients
Authors: Chang Chih-Chao , Vlad George , Vasilescu Elena Rodica , Li Ping , Husain Syed A. , Silvia Elaine A. , Cohen David J , Ratner Lloyd E. , Sun Wei-Zen , Mohan Sumit , Suciu-Foca Nicole
Published: April 2022

The SARS-CoV-2 pandemic poses a great threat to global health, particularly in solid organ transplant recipients (SOTRs). Although a 3-dose mRNA vaccination protocol has been implemented for the majority of SOTRs, its effectiveness was still largely unknown. We analyzed 113 vaccinated SOTRs, and 30 healthy controls (HCs), some of whom had recovered from COVID, for their immune responses against the original vaccine strain and variants of concern (VOC), including the highly mutated-omicron variant. Here, we report that 3 doses of the mRNA vaccine had only a modest effect in eliciting anti-viral responses against all viral strains in the fully vaccinated SOTRs who did not contract the virus. Only 34.0% (16/47) of this group of patients demonstrated both detectable anti-RBD IgG and neutralization activities against alpha, beta, and delta variants, and only 8.5% (4/47) of them showed additional omicron-neutralizing capacities. In contrast, 79.5% (35/44) of the vaccinated recovered-SOTRs demonstrated both higher anti-RBD IgG levels and neutralizing activities against all VOC, including omicron. These findings illustrate a significant impact of previous infection on the development of anti-COVID immune responses in vaccinated SOTRs and highlight the need for alternative strategies to protect a subset of a lesser-vaccine responsive population.
Distinct metabolic features of genetic liability to type 2 diabetes and coronary artery disease: a reverse Mendelian randomization study
Authors: Smith Madeleine L , Bull Caroline J , Holmes Michael V , Davey Smith George , Anderson Emma L , Bell Joshua A
Published: April 2022

Type 2 diabetes (T2D) and coronary artery disease (CAD) both have known genetic determinants, but the mechanisms through which their associated genetic variants lead to disease onset remain poorly understood. Here, we used large-scale metabolomics data to directly compare the metabolic features of genetic liability to T2D and to CAD. We performed two-sample reverse Mendelian randomization (MR) to estimate effects of genetic liability to T2D and CAD on 249 circulating metabolites from targeted nuclear magnetic resonance spectroscopy in the UK Biobank (N=118,466). We examined the potential for medication use to distort effect estimates by examining effects of disease liability on metformin and statin use and by conducting age-stratified metabolite analyses. Using inverse variance weighted (IVW) models, higher genetic liability to T2D was estimated to decrease high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) (e.g., HDL-C: -0.05 SD; 95% CI -0.07, -0.03, per doubling of liability), whilst increasing all triglyceride groups and branched chain amino acids (BCAAs). Estimates for CAD liability suggested an effect on reducing HDL-C as well as raising very-low density lipoprotein cholesterol (VLDL-C) and LDL-C, and LDL triglycerides. Liability to each disease was estimated to decrease apolipoprotein-A1, whilst only CAD liability was estimated with IVW to increase apolipoprotein-B (0.10 SD; 95% CI 0.03, 0.17). In pleiotropy-robust sensitivity models, T2D liability was still estimated to increase BCAAs, but several effect estimates for higher CAD liability reversed and supported decreased LDL-C and apolipoprotein-B. Estimated effects of CAD liability differed uniquely and substantially by age for non-HDL-C traits in particular, with, e.g., pleiotropy-robust models suggesting that higher CAD liability lowers LDL-C only at older ages when use of statins is common. Our results from pleiotropy-robust models support largely distinct metabolic features of genetic liability to T2D and to CAD, particularly higher BCAAs in T2D and lower LDL-C and apolipoprotein-B in CAD. Such apparently favourable effects of CAD liability differ substantially by age and likely reflect mediation by statin use in adulthood.
Genetic risk and incident venous thromboembolism in middle-aged and older adults following Covid-19 vaccination
Authors: Xie Junqing , Prats-Uribe Albert , Maranon Maria Gordillo , Strauss Victoria Y. , Gill Dipender , Prieto-Alhambra Daniel
Published: April 2022

BACKGROUND

Covid-19 vaccination has been associated with an increased risk of venous thromboembolism (VTE). However, it is unknown whether genetic predisposition to VTE is associated with an increased risk of thrombosis following vaccination.

METHODS

Using data from the UK Biobank, which contains in-depth genotyping data and linked vaccination and health outcomes information, we generated a polygenic risk score (PRS) using 299 genetic variants identified from a previous large genome-wide association study. We prospectively assessed associations between PRS and incident VTE after first and the second-dose vaccination separately. We conducted sensitivity analyses stratified by vaccine type (adenovirus- and mRNA-based) and using two historical unvaccinated cohorts. We estimated hazard ratios (HR) for PRS-VTE associations using Cox models.

RESULTS

Of 359,310 individuals receiving one dose of a Covid-19 vaccine, 160,327 (44.6%) were males, and the mean age at the vaccination date was 69.05 (standard deviation [SD] 8.04) years. After 28- and 90-days follow-up, 88 and 299 individuals developed VTE respectively, equivalent to an incidence rate of 0.88 (95% confidence interval [CI] 0.70 to 1.08) and 0.92 (95% CI 0.82 to 1.04) per 100,000 person-days. The PRS was significantly associated with a higher risk of VTE (HR per 1 SD increase in PRS, 1.41 (95% CI 1.15 to 1.73) in 28 days and 1.36 (95% CI 1.22 to 1.52) in 90 days). Similar associations were found after stratification by vaccine type, in the two-dose cohort and across the historical unvaccinated cohorts.

CONCLUSIONS

The genetic determinants of post-Covid-19-vaccination VTE are similar to those seen in historical data. This suggests that, at the population level, post-vaccine VTE has similar aetiology to conventional VTE. Additionally, the observed PRS-VTE associations were equivalent for adenovirus- and mRNA-based vaccines.
The ETKA study - Impact of early therapy termination on treated phonemes in conversational speech tasks in children aged 5 to 6 years with phonologically delayed development: protocol for a multicenter randomized controlled trial
Authors: Detter-Biesl Doris , Schwartz Bernhard
Published: April 2022

Background

Children with speech and language disorders frequently display speech sound disorders, the treatment of which improves children’s ability to communicate. However, there is a significant gap between those therapy capacities needed and those provided in Austria. In addition, as the effect of early therapy termination has not yet been systematically evaluated, the aim of this project is to investigate the influence of an early therapy termination on phonological processes in children aged 5 to 6 years with phonologically delayed development.

Methods/Design

Forty 5- to 6-year-old children, currently participating in speech therapies in the Upper Austrian region will participate in this multicenter randomized controlled trial. The participants will be randomly allocated to either the intervention group (early therapy termination) or the control group (uninterrupted ongoing therapy) by envelop randomization. Phoneme accuracy in spontaneous speech determined during 15 minutes of conversational sampling and phoneme accuracy for single-word production determined with the PLAKKS assessment will be used to assess therapy efficacy. The results from both groups will be compared regarding the correct use of the target phoneme/consonant cluster in conversational speech situation.

Discussion

This study will explore the effect of early therapy termination on speech sound disorders in 5- to 6-yearold children. If an early termination exhibits non-inferiority to the current ongoing therapy, therapy resources could be used more effectively. Subsequently, earlier therapy starts for more children could be facilitated and negative consequences of delayed therapies could be counteracted.

Ethics and dissemination

The study was approved by an institutional review board (ID: A-2019-035). Dissemination will be achieved through peer-review conferences and journals.

Trial registration

The study is registered at ClinicalTrials.gov (Identifier: NCT03972891, Registered 4 June 2019, https://www.clinicaltrials.gov/ct2/show/NCT03972891).
COVID-19 vaccine effectiveness against severe disease from the Omicron BA.1 and BA.2 subvariants – surveillance results from southern Sweden, December 2021 to March 2022
Authors: Björk Jonas , Bonander Carl , Moghaddassi Mahnaz , Rasmussen Magnus , Malmqvist Ulf , Inghammar Malin , Kahn Fredrik
Published: April 2022

We compared vaccine effectiveness (VE) against severe COVID-19 during calendar periods from December 2021 to March 2022 when Omicron BA.1 and BA.2, respectively, were the dominating virus variants in Scania county, Sweden. We used continuous density case-control sampling matched for sex and age, and with further adjustment for differences in comorbidities and prior infection. VE remained relatively stable after the transition from BA.1 to BA.2 among people with at least three doses but decreased markedly among those with only two doses. Protection from prior infection was also lower after the transition to BA.2. These findings suggest that booster vaccination is needed to maintain sufficient protection against severe COVID-19.
EHR Foundation Models Improve Robustness in the Presence of Temporal Distribution Shift
Authors: Guo Lin Lawrence , Steinberg Ethan , Fleming Scott Lanyon , Posada Jose , Lemmon Joshua , Pfohl Stephen R , Shah Nigam , Fries Jason , Sung Lillian
Published: April 2022

Background

Temporal distribution shift negatively impacts the performance of clinical prediction models over time. Pretraining foundation models using self-supervised learning on electronic health records (EHR) may be effective in acquiring informative global patterns that can improve the robustness of task-specific models.

Objective

To evaluate the utility of EHR foundation models in improving the in-distribution (ID) and out-of-distribution (OOD) performance of clinical prediction models.

Methods

The cohort consisted of adult inpatients admitted between 2009-2021. Gated recurrent unit (GRU)- and transformer (TRANS)-based foundation models were pretrained on EHR of patients admitted between 2009-2012 and were subsequently used to construct patient representations (CLMBR). These representations were used to learn logistic regression models (CLMBRGRU and CLMBRTRANS) to predict hospital mortality, long length of stay, 30-day readmission, and ICU admission. We compared CLMBRGRU and CLMBRTRANS with baseline logistic regression models learned on count-based representations (count-LR) and end-to-end (ETE) GRU and transformer models in ID (2009-2012) and OOD (2013-2021) year groups. Performance was measured using area-under-the-receiver-operating-characteristic curve, area- under-the-precision-recall curve, and absolute calibration error.

Results

Models trained on CLMBR generally showed better discrimination relative to count-LR in both ID and OOD year groups. In addition, they often matched or were better than their ETE counterparts. Finally, foundation models’ performance in the self-supervised learning task tracked closely with the ID and OOD performance of the downstream models.

Conclusions

These results suggest that pretraining foundation models on electronic health records is a useful approach for developing clinical prediction models that perform well in the presence of temporal distribution shift.
Effect of SARS-CoV-2 digital droplet RT-PCR assay sensitivity on COVID-19 wastewater based epidemiology
Authors: Kim Sooyeol , Wolfe Marlene K. , Criddle Craig S. , Duong Dorothea H. , Chan-Herur Vikram , White Bradley J. , Boehm Alexandria B.
Published: April 2022

We developed and implemented a framework for examining how molecular assay sensitivity for a viral RNA genome target affects its utility for wastewater-based epidemiology. We applied this framework to digital droplet RT-PCR measurements of SARS-CoV-2 and Pepper Mild Mottle Virus genes made using 10 replicate wells, and determined how using fewer wells affected assay sensitivity and its performance for wastewater-based epidemiology applications. We used a computational, downsampling approach. When percent of positive droplets was between 0.024% and 0.5% (as was the case for SARS-CoV-2 genes during the Delta surge), measurements obtained with 3 or more wells were similar to those obtained using 10. When percent of positive droplets was less than 0.024%, then 6 or more wells were needed to obtain similar results as those obtained using 10 wells. When COVID-19 incidence is low, as it was before the Delta surge and SARS-CoV-2 gene concentrations are <104 cp/g, using 6 wells will yield a detectable concentration 90% of the time. Overall, results support an adaptive approach where assay sensitivity is increased by running 6 or more wells during periods of low SARS-CoV-2 gene concentrations, and 3 or more wells during periods of high SARS-CoV-2 gene concentrations.

Synopsis

Adaptive approaches developed with assay sensitivity in consideration may reduce cost and increase sensitivity for wastewater-based epidemiology.

Abstract Art
A Model to Predict In-hospital Mortality in Elderly Patients with Community-acquired Pneumonia: a Retrospective Study
Authors: Hao Yanting , Zhang Hua , Yan Yingying , Zhu Yun , Zhang Fuchun
Published: April 2022

Objectives

To develop and validate a predictive model for evaluating in-hospital mortality risk in elderly patients with community-acquired pneumonia.

Setting

Two tertiary care hospitals with 2000 beds and 1000 beds respectively in Beijing, China.

Participants

Elderly patients (age ≥ 65 years) with community-acquired pneumonia admitted to the Department of Internal Medicine of the two hospitals from January 2010 to December 2019 or from January 2019 to December 2019 respectively.

Design

It was a retrospective study. After dividing the data set into training and validation sets, we created a mortality model that included patient demographics, hospitalization time, hospital outcome, and various clinical conditions associated with hospitalization. We then applied the model to the validation set.

Main outcome measures

In-hospital mortality.

Results

The training cohort included 2,466 patients admitted to the one hospital, while the validation cohort included 424 patients at the other hospital. The overall in-hospital mortality rate was 15.6%. In the multivariable model, age, respiratory failure, heart failure, and malignant tumors were associated with mortality. The model had excellent discrimination with AUC values of 0.877 and 0.930 in the training and validation cohorts, respectively.

Conclusions

The predictive model to evaluate in-hospital mortality in elderly patients with community-acquired pneumonia, which was established based on administrative data, provides a simple tool for physicians to assess the prognosis of elderly patients with community-acquired pneumonia in Beijing.

Strengths and limitations of this study

The clinical data collected were obtained from a large retrospective cohort over a 10-year period, resulting in good reliability.

The model based on administrative data can help healthcare workers determine the prognosis and outcomes of elderly patients of CAP, especially in resource limited regions in China.

Our main outcome was in-hospital mortality, not 30-day mortality or longer.

All included cases were collected from inpatient, outpatient and emergency patients were not included.

The model was only verified in two hospitals in Beijing and further verification should be conducted in other areas and different levels of hospitals.
A boost with SARS-CoV-2 BNT162b2 mRNA vaccine elicits strong humoral responses independently of the interval between the first two doses
Authors: Tauzin Alexandra , Gong Shang Yu , Painter Mark M. , Goel Rishi R. , Chatterjee Debashree , Beaudoin-Bussières Guillaume , Marchitto Lorie , Boutin Marianne , Laumaea Annemarie , Okeny James , Gendron-Lepage Gabrielle , Bourassa Catherine , Medjahed Halima , Goyette Guillaume , Williams Justine C. , Bo Yuxia , Gokool Laurie , Morrisseau Chantal , Arlotto Pascale , Bazin Renée , Fafard Judith , Tremblay Cécile , Kaufmann Daniel E. , De Serres Gaston , Côté Marceline , Duerr Ralf , Martel-Laferrière Valérie , Greenplate Allison R. , Wherry E. John , Finzi Andrés
Published: April 2022

Due to the recrudescence of SARS-CoV-2 infections worldwide, mainly caused by Omicron BA.1 and BA.2 variants of concern, several jurisdictions are administering a mRNA vaccine boost. Here, we analyzed humoral responses induced after the second and third doses of mRNA vaccine in naïve and previously-infected donors who received their second dose with an extended 16-week interval. We observed that the extended interval elicited robust humoral responses against VOCs, but this response was significantly diminished 4 months after the second dose. Administering a boost to these individuals brought back the humoral responses to the same levels obtained after the extended second dose. Interestingly, we observed that administering a boost to individuals that initially received a short 3-4 weeks regimen elicited humoral responses similar to those elicited in the long interval regimen. Nevertheless, humoral responses elicited by the boost in naïve individuals did not reach those present in previously-infected vaccinated individuals.
WFA-GPU: Gap-affine pairwise alignment using GPUs
Authors: Aguado-Puig Quim , Doblas Max , Matzoros Christos , Espinosa Antonio , Moure Juan Carlos , Marco-Sola Santiago , Moreto Miquel
Published: April 2022

Motivation

Advances in genomics and sequencing technologies demand faster and more scalable analysis methods that can process longer sequences with higher accuracy. However, classical pairwise alignment methods, based on dynamic programming (DP), impose impractical computational requirements to align long and noisy sequences like those produced by PacBio, and Nanopore technologies. The recently proposed WFA algorithm paves the way for more efficient alignment tools, improving time and memory complexity over previous methods. However, high-performance computing (HPC) platforms require efficient parallel algorithms and tools to exploit the computing resources available on modern accelerator-based architectures.

Results

This paper presents the WFA-GPU, a GPU (Graphics Processing Unit)-accelerated tool to compute exact gap-affine alignments based on the WFA algorithm. We present the algorithmic adaptations and performance optimizations that allow exploiting the massively parallel capabilities of modern GPU devices to accelerate the alignment computations. In particular, we propose a CPU-GPU co-design capable of performing inter-sequence and intra-sequence parallel sequence alignment, combining a succinct WFA-data representation with an efficient GPU implementation. As a result, we demonstrate that our implementation outperforms the original multi-threaded WFA implementation between 1.5-7.7× and up to 17× when using heuristic methods on long and noisy sequences. Compared to other state-of-the-art tools and libraries, the WFA-GPU is up to 29× faster than other GPU implementations and up to four orders of magnitude faster than other CPU implementations.

Availability

WFA-GPU code and documentation are publicly available athttps://github.com/quim0/WFA-GPU.

Contact

quim.aguado@uab.cat
Comparative analysis of temperature preference behavior and effects of temperature on daily behavior in eleven Drosophila species
Authors: Ito Fumihiro , Awasaki Takeshi
Published: April 2022

Temperature is one of the most critical environmental factors that influence various biological processes. Species distributed in different temperature regions are considered to have different optimal temperatures for daily life activities. However, how organisms have acquired various features to cope with particular temperature environments remains to be elucidated. In this study, we have systematically analyzed the temperature preference behavior and effects of temperatures on daily locomotor activity and sleep using 11 Drosophila species. We also investigated the function of antennae in the temperature preference behavior of these species. We found that, (1) an optimal temperature for daily locomotor activity and sleep of each species approximately matches with temperatures it frequently encounters in its habitat, (2) effects of temperature on locomotor activity and sleep are diverse among species, but each species maintains its daily activity and sleep pattern even at different temperatures, and (3) each species has a unique temperature preference behavior, and the contribution of antennae to this behavior is diverse among species. These results suggest that Drosophila species inhabiting different climatic environments have acquired species-specific temperature response systems according to their life strategies. This study provides fundamental information for understanding the mechanisms underlying their temperature adaptation and lifestyle diversification.
Antibody escape and cryptic cross-domain stabilization in the SARS-CoV-2 Omicron spike protein
Authors: Javanmardi Kamyab , Segall-Shapiro Thomas H. , Chou Chia-Wei , Boutz Daniel R. , Olsen Randall J. , Xie Xuping , Xia Hongjie , Shi Pei-Yong , Johnson Charlie D. , Annapareddy Ankur , Weaver Scott , Musser James M. , Ellington Andrew D. , Finkelstein Ilya J. , Gollihar Jimmy D.
Published: April 2022

The worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the repeated emergence of variants of concern. The Omicron variant has two dominant sub-lineages, BA.1 and BA.2, each with unprecedented numbers of nonsynonymous and indel spike protein mutations: 33 and 29, respectively. Some of these mutations individually increase transmissibility and enhance immune evasion, but their interactions within the Omicron mutational background is unknown. We characterize the molecular effects of all Omicron spike mutations on expression, human ACE2 receptor affinity, and neutralizing antibody recognition. We show that key mutations enable escape from neutralizing antibodies at a variety of epitopes. Stabilizing mutations in the N-terminal and S2 domains of the spike protein compensate for destabilizing mutations in the receptor binding domain, thereby enabling the record number of mutations in Omicron sub-lineages. Taken together, our results provide a comprehensive account of the mutational effects in the Omicron spike protein and illuminate previously unknown mechanisms of how the N-terminal domain can compensate for destabilizing mutations within the more evolutionarily constrained RBD.
gr Predictor: a Deep-Learning Model for Predicting the Hydration Structures around Proteins
Authors: Kawama Kosuke , Fukushima Yusaku , Ikeguchi Mitsunori , Ohta Masateru , Yoshidome Takashi
Published: April 2022

Among the factors affecting biological processes such as protein folding and ligand binding, hydration, which is represented by a three-dimensional water-site-distribution-function around the protein, is crucial. The typical methods for computing the distribution functions, including molecular dynamics simulations and the three-dimensional reference interaction site model (3D-RISM) theory, require a long computation time from hours to tens of hours. Here, we propose a deep-learning model rapidly estimating the distribution functions around proteins obtained by the 3D-RISM theory from the protein 3D structure. The distribution functions predicted using our deep-learning model are in good agreement with those obtained by the 3D-RISM theory. Particularly, the coefficient of determination between the distribution function obtained by the deep-learning model and that obtained using the 3D-RISM theory is approximately 0.98. Furthermore, using a graphics processing unit (GPU), the calculation by the deep learning model is completed in less than one minute, more than 2 orders of magnitude faster than the calculation time of 3D-RISM theory. Therefore, our deep learning model provides a practical and efficient way to calculate the three-dimensional water-site-distribution-functions. The program called “gr Predictor” is available under the GNU General Public License from https://github.com/YoshidomeGroup-Hydration/gr-predictor.

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Population Dynamics of Immunological Synapse Formation Induced by Bispecific T-cell Engagers Predict Clinical Pharmacodynamics and Treatment Resistance
Authors: Liu Can , Zhou Jiawei , Kudlacek Stephan , Qi Timothy , Dunlap Tyler , Cao Yanguang
Published: April 2022

Effector T cells form immunological synapses (IS) with recognized target cells to elicit cytolytic effects. Facilitating IS formation is the principal pharmacological action of most T cell-based cancer immunotherapies. However, the dynamics of IS formation at the cell population level, the primary driver of the pharmacodynamics of many cancer immunotherapies, remains poorly defined. With classic immunotherapy CD3/CD19 bispecific T cell engager (BiTE) as a model system, we integrate experimental and theoretical approaches to investigate the population dynamics of IS formation and their relevance to clinical pharmacodynamics and treatment resistance. Our models produce experimentally consistent predictions when defining IS formation as a series of spatiotemporally coordinated events driven by molecular and cellular interactions. The models predict tumor-killing pharmacodynamics in patients and reveal trajectories of tumor evolution across anatomical sites under BiTE immunotherapy. Our model highlight the bone marrow may serve as a sanctuary site permitting tumor evolution and antigen escape. The models also suggest the optimal dosing regimens as a function of tumor growth and patient T cell abundance that confer adequate tumor control with minimal disease evolution. This work has implications for developing more effective T cell-based cancer immunotherapies.
NETSCOPE: Information-Theory based Network Discovery and Analysis
Authors: Bergmans Tido , Jamal Tousif , Celikel Tansu
Published: April 2022

Molecular, cellular, structural, and functional networks in the brain each represent different levels of organization and complexity. These networks are interconnected, and their interactions underlie the brain’s abilities to process information, regulate bodily functions, and mediate behavior. While understanding the emergence of higher-level networks (structural and functional) from the interactions of lower-level (molecular and cellular) ones is crucial, a universal analytical method applicable to all brain network types has been lacking. Here we introduce an open-source toolbox (NETSCOPE) that identifies weighted network architectures using mutual information (MI) and variation of information (VI). We demonstrate the accuracy of the resulting networks using synthetic data and by recreating five molecular networks in S. cerevisiae. We finally deploy NETSCOPE to identify cell type specific transcriptional networks and reconstruct the brain-wide neural networks that encode touch in the mouse brain. The code is made available in Python, Google Colab, Jupyter Notebook, MATLAB, and Octave. Beyond its core functionality, this network discovery method holds potential for broader applications, including the development of bioinspired sparse artificial networks.
Phertilizer: Growing a Clonal Tree from Ultra-low Coverage Single-cell DNA Sequencing of Tumors
Authors: Weber Leah L. , Zhang Chuanyi , Ochoa Idoia , El-Kebir Mohammed
Published: April 2022

Emerging ultra-low coverage single-cell DNA sequencing (scDNA-seq) technologies have enabled high resolution evolutionary studies of copy number aberrations (CNAs) within tumors. While these sequencing technologies are well suited for identifying CNAs due to the uniformity of sequencing coverage, the sparsity of coverage poses challenges for the study of single-nucleotide variants (SNVs). In order to maximize the utility of increasingly available ultra-low coverage scDNA-seq data and obtain a comprehensive understanding of tumor evolution, it is important to also analyze the evolution of SNVs from the same set of tumor cells.

We present Phertilizer, a method to infer a clonal tree from ultra-low coverage scDNA-seq data of a tumor. Based on a probabilistic model, our method recursively partitions the data by identifying key evolutionary events in the history of the tumor. We demonstrate the performance of Phertilizeron simulated data as well as on two real datasets, finding that Phertilizereffectively utilizes the copynumber signal inherent in the data to more accurately uncover clonal structure and genotypes compared to previous methods.

Availability

https://github.com/elkebir-group/phertilizer
Sirtuin gene isoforms and genomic sequences of mouse and humans: Divergence across species
Authors: Zhang Xiaomin , Azhar Gohar , Ameer Fathima S. , Crane Jasmine , Wei Jeanne Y.
Published: April 2022

Background

There are seven sirtuin genes in the mammalian genome. Each sirtuin gene contains multiple exons, and is likely to undergo alternative splicing, thereby increasing sirtuin gene diversity. Since the alternatively spliced isoforms tend to increase with advancing age, it is important to study the effect of sequence change on isoform function. Additionally, the divergence of isoform patterns between human and mouse will help us to properly interpret the findings from animal models, especially in age-related studies. Recently, more than 20 human sirtuin isoforms have been identified, but whether the mouse genome might have similar isoforms remains incompletely established.

Methods

The mRNA, protein and genomic DNA sequences of mouse sirtuin genes, as well as the transcription factor binding sites, including that of SRF, were analyzed. A cellular stress model with serum deprivation and restoration was used to reflect the blood supply and nutrients level changes in the ischemia and reperfusion condition, and the expression of sirtuin isoform was assessed.

Results

Here, we report the identification of 15 mouse sirtuin isoforms, of which over half have not been previously reported. Exon skipping was the main event, which led to domain losses in the nuclear localization signal, nucleolar localization signal, and/or the mitochondrial targeting sequence among sirtuin isoforms. Among 7 sirtuin genes, 6 mouse sirtuin genes had different exon numbers versus that of human sirtuin genes. Only the sirtuin-2 gene had the same number of exons in both human and mouse. However, there were differences in the sirtuin-2 gene isoforms and the regulatory domains between the two species. The expression of sirtuin gene isoforms under serum stress was also different.

Conclusions

Alternative splicing increases both sirtuin transcriptome and proteome diversity. However, the sirtuin isoforms were not well conserved between human and mouse, which should be taken into consideration when extrapolating animal studies for human physiology and pathology. Our results will help to elucidate the role of sirtuin genes in the regulation of cellular stress response, including ischemia and reperfusion. We propose that the existence of the CArG and CArG-like sequences in sirtuin genes may imply a role for SRF in the sirtuin family transcriptional regulation.
A coupled atrioventricular-aortic setup for in-vitro hemodynamic study of the systemic circulation: Design, Fabrication, and Physiological relevancy
Authors: Alavi Rashid , Aghilinejad Arian , Wei Heng , Niroumandi Soha , Wieman Seth , Pahlevan Niema M
Published: April 2022

In-vitro models of the systemic circulation have gained a lot of interest for fundamental understanding of cardiovascular dynamics and for applied hemodynamic research. In this study, we introduce a physiologically accurate in-vitro hydraulic setup that models the hemodynamics of the coupled atrioventricular-aortic system. This unique experimental simulator has three major components: 1) an arterial system consisting of a human-scale artificial aorta along with the main branches, 2) an artificial left ventricle (LV) sac connected to a programmable piston-in-cylinder pump for simulating cardiac contraction and relaxation, and 3) an artificial left atrium (LA). The setup is designed in such a way that the basal LV is directly connected to the aortic root via an aortic valve, and to the LA via an artificial mitral valve. As a result, two-way hemodynamic couplings can be achieved for studying the effects that the LV, aorta, and LA have on each other. The collected pressure and flow measurements from this setup demonstrate a remarkable correspondence to clinical hemodynamics. We also investigate the physiological relevancies of isolated effects on cardiovascular hemodynamics of various major global parameters found in the circulatory system, including LV contractility, LV preload, heart rate, aortic compliance, and peripheral resistance. Subsequent control over such parameters ultimately captures physiological hemodynamic effects of LV systolic dysfunction, preload (cardiac) diseases, and afterload (arterial) diseases. The detailed design and fabrication of the proposed setup is also provided.
Genome-wide detection of human variants that disrupt intronic branchpoints
Authors: Zhang Peng , Philippot Quentin , Ren Weicheng , Lei Wei-Te , Li Juan , Stenson Peter D. , Palacín Pere Soler , Colobran Roger , Boisson Bertrand , Zhang Shen-Ying , Puel Anne , Pan-Hammarström Qiang , Zhang Qian , Cooper David N. , Abel Laurent , Casanova Jean-Laurent
Published: April 2022

Pre-mRNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Fifty-six rare variants in 44 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach has been available to efficiently detect such variants in next-generation sequencing (NGS) data. We established a comprehensive human genome-wide BP database by integrating existing BP data, and by generating new BP data from RNA-seq of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We in-depth characterize multiple features of BP in major and minor introns, and find that BP and BP-2 (two-nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, whilst being comparable to the exonic background. We develop BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition in NGS data. BPHunter retrospectively identifies 48 of the 56 known pathogenic BP mutations in which we summarize a strategy for prioritizing BP mutation candidates, and the remaining 8 all create AG dinucleotides between BP and acceptor site which is probably the reason for mis-splicing. We demonstrate the utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia, and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which we validate experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter.
Flexible control of representational dynamics in a disinhibition-based model of decision making
Authors: Shen Bo , Louie Kenway , Glimcher Paul
Published: April 2022

Current models utilize two primary circuit motifs to replicate neurobiological decision making. Recurrent gain control implements normalization-driven relative value coding, while recurrent excitation and non-selective pooled inhibition together implement winner-take-all (WTA) dynamics. Despite evidence for concurrent valuation and selection computations in individual brain regions, existing models focus selectively on either normalization or WTA dynamics and how both arise in a single circuit architecture is unknown. Here we show that a novel hybrid motif unifies both normalized representation and WTA competition, with dynamic control of circuit state governed by local disinhibition. In addition to capturing empirical psychometric and chronometric data, the model produces persistent activity consistent with working memory. Furthermore, the biological basis of disinhibition provides a simple mechanism for flexible top-down control of network states, enabling the circuit to capture diverse task-dependent neural dynamics. These results suggest a new biologically plausible mechanism for decision making and emphasize the importance of local disinhibition in neural processing.