bluuebunny/crossref_metadata_2025 huggingface dataset:
Prioritizing virtual screening with interpretable interaction fingerprints
Authors: Fassio Alexandre V. , Shub Laura , Ponzoni Luca , McKinley Jessica , O’Meara Matthew J. , Ferreira Rafaela S. , Keiser Michael J. , de Melo Minardi Raquel C.
Published: May 2022

Machine learning-based drug discovery success depends on molecular representation. Yet traditional molecular fingerprints omit both the protein and pointers back to structural information that would enable better model interpretability. Therefore, we propose LUNA, a Python 3 toolkit that calculates and encodes protein-ligand interactions into new hashed fingerprints inspired by Extended Connectivity Finger-Print (ECFP): EIFP (Extended Interaction FingerPrint), FIFP (Functional Interaction FingerPrint), and Hybrid Interaction FingerPrint (HIFP). LUNA also provides visual strategies to make the fingerprints interpretable. We performed three major experiments exploring the fingerprints’ use. First, we trained machine learning models to reproduce DOCK3.7 scores using 1 million docked Dopamine D4 complexes. We found thatEIFP-4,096performed (R2= 0.61) superior to related molecular and interaction fingerprints. Secondly, we used LUNA to support interpretable machine learning models. Finally, we demonstrate that interaction fingerprints can accurately identify similarities across molecular complexes that other fingerprints over-look. Hence, we envision LUNA and its interface fingerprints as promising methods for machine learning-based virtual screening campaigns. LUNA is freely available athttps://github.com/keiserlab/LUNA.
NeRFax: An efficient and scalable conversion from the internal representation to Cartesian space
Authors: Dutton Oliver , Hoffmann Falk , Tamiola Kamil
Published: May 2022

Motivation

Accurate modelling of protein ensembles requires sampling of a large number of 3D conformations. A number of sampling approaches that use internal coordinates have been proposed, yet poor performance in the conversion from internal to Cartesian coordinates limits their applicability.

Results

We describe here NeRFax, an efficient method for the conversion from internal to Cartesian coordinates that utilizes the platform-agnostic JAX Python library. The relative benefit of NeRFax is demonstrated here, on peptide chain reconstruction tasks. Our novel approach offers 35-175x times performance gains compared to previous state-of-the-art methods, whereas >10,000x speedup is reported in a reconstruction of a biomolecular condensate of 1,000 chains.

Availability

NeRFax has purely open-source dependencies and is available at https://github.com/PeptoneLtd/nerfax.

Contact

oliver@peptone.io
Undermatching is a consequence of policy compression
Authors: Bari Bilal A. , Gershman Samuel J.
Published: May 2022

The matching law describes the tendency of agents to match the ratio of choices allocated to the ratio of rewards received when choosing among multiple options (Herrnstein, 1961). Perfect matching, however, is infrequently observed. Instead, agents tend to undermatch, or bias choices towards the poorer option. Overmatching, or the tendency to bias choices towards the richer option, is rarely observed. Despite the ubiquity of undermatching, it has received an inadequate normative justification. Here, we assume agents not only seek to maximize reward, but also seek to minimize cognitive cost, which we formalize as policy complexity (the mutual information between actions and states of the environment). Policy complexity measures the extent to which an agent’s policy is state-dependent. Our theory states that capacity-constrained agents (i.e., agents that must compress their policies to reduce complexity), can only undermatch or perfectly match, but not overmatch, consistent with the empirical evidence. Moreover, we validate a novel prediction about which task conditions exaggerate undermatching. Finally, we argue that a reduction in undermatching with higher dopamine levels in patients with Parkinson’s disease is consistent with an increased policy complexity.

Significance statement

The matching law describes the tendency of agents to match the ratio of choices allocated to different options to the ratio of reward received. For example, if option A yields twice as much reward as option B, matching states that agents will choose option A twice as much. However, agents typically undermatch: they choose the poorer option more frequently than expected. Here, we assume that agents seek to simultaneously maximize reward and minimize the complexity of their action policies. We show that this theory explains when and why undermatching occurs. Neurally, we show that policy complexity, and by extension undermatching, is controlled by tonic dopamine, consistent with other evidence that dopamine plays an important role in cognitive resource allocation.
A comparison of software for analysis of rare and common short tandem repeat (STR) variation using human genome sequences from clinical and population-based samples
Authors: Oketch John W. , Wain Louise V. , Hollox Edward J.
Published: May 2022

Short tandem repeat (STR) variation is an often overlooked source of variation between genomes. STRs comprise about 3% of the human genome and are highly polymorphic. Some cause Mendelian disease, and others affect gene expression. Their contribution to common disease is not well-understood, but recent software tools designed to genotype STRs using short read sequencing data are beginning to address this. Here, we compare software that genotypes common STRs and rarer STR expansions genome-wide, with the aim of applying them to population-scale genomes. By using the Genome-In-A-Bottle (GIAB) consortium and 1000 Genomes Project sequencing data, we compare performance in terms of sequence length, depth, computing resources needed, genotyping accuracy and number of STRs genotyped. To ensure broad applicability of our findings, we also measure genotyping performance against a set of genomes from clinical samples with known STR expansions, and a set of STRs commonly used for forensic identification. We find that HipSTR, ExpansionHunter and GangSTR perform well in genotyping common STRs, including the CODIS 13 core STRs used for forensic analysis. GangSTR and ExpansionHunter outperform HipSTR for genotyping call rate and memory usage. ExpansionHunter denovo (EHdn), STRling and GangSTR outperformed STRetch for detecting expanded STRs, and EHdn and STRling used considerably less processor time compared to GangSTR. Analysis on shared genomic sequence data provided by the GIAB consortium allows future performance comparisons of new software approaches on a common set of data, facilitating comparisons and allowing researchers to choose the best software that fulfils their needs.
PACeR: a bioinformatic pipeline for the analysis of chimeric RNA-seq data
Authors: Mills William T , Jaffe Andrew E. , Meffert Mollie K
Published: May 2022

MicroRNAs (miRNAs) are small non-coding RNAs that function in post-transcriptional gene regulation through imperfect base pairing with mRNA targets which results in inhibition of translation and often destabilization of bound transcripts. Sequence-based algorithms historically used to predict miRNA targets face inherent challenges in reliably reflecting in vivo interactions. Recent strategies have directly profiled miRNA-target interactions by cross-linking and ligation of miRNAs to their targets within the RNA-induced silencing complex (RISC), followed by high throughput sequencing of the chimeric RNAs. Despite the strength of these direct chimeric miRNA:target profiling approaches, standardized pipelines for analyzing the resulting chimeric RNA sequencing data are not readily available. Here we present PACeR, a robust bioinformatic pipeline for the analysis of chimeric RNA sequencing data. PACeR consists of two parts, each of which are optimized for the distinctive characteristics of chimeric RNA sequencing reads: first, read processing and alignment and second, peak calling and motif analysis. We apply PACeR to chimeric RNA sequencing data generated in our lab as well as a published benchmark dataset. PACeR has minimal computational power requirements and contains extensive annotation to broaden accessibility for processing chimeric RNA sequencing data and enable insights to be gained about the targets of small non-coding RNAs in regulating diverse biological systems.
G protein-coupled receptor 151 regulates glucose metabolism and hepatic gluconeogenesis
Authors: Bielczyk-Maczynska Ewa , Zhao Meng , Zushin Peter-James H. , Schnurr Theresia M. , Kim Hyun-Jung , Li Jiehan , Nallagatla Pratima , Sangwung Panjamaporn , Park Chong , Cornn Cameron , Stahl Andreas , Svensson Katrin J. , Knowles Joshua W.
Published: May 2022

Human genetics has been instrumental in identification of genetic variants linked to type 2 diabetes (T2D). Recently a rare, putative loss-of-function mutation in the orphan G-protein coupled receptor 151 (GPR151) was found to be associated with lower odds ratio for T2D, but the mechanism behind this association has remained elusive. Here for the first time we show that Gpr151 is a fasting- and glucagon-responsive hepatic gene which regulates hepatic gluconeogenesis. Gpr151 ablation in mice leads to suppression of hepatic gluconeogenesis genes and reduced hepatic glucose production in response to pyruvate. Importantly, the restoration of hepatic Gpr151 levels in the Gpr151 knockout mice reverses the reduced hepatic glucose production. Our findings establish a previously unknown role of Gpr151 in the liver and provides an explanation to the lowered T2D risk in individuals with nonsynonymous mutations in GPR151. This study highlights the therapeutic potential of targeting GPR151 for treatment of metabolic disease.
REM Sleep Movements in Parkinson’s Disease: Is the Basal Ganglia Engaged?
Authors: Verma Ajay K. , Acosta Lenis Sergio Francisco , Aman Joshua E. , Sanabria David Escobar , Wang Jing , Pearson Amy , Hill Meghan , Patriat Remi , Schrock Lauren E. , Cooper Scott E. , Park Michael C. , Harel Noam , Howell Michael J. , MacKinnon Colum D. , Vitek Jerrold L. , Johnson Luke A.
Published: May 2022

To elucidate the role of the basal ganglia during REM sleep movements in Parkinson’s disease (PD) we recorded pallidal neural activity from four PD patients. Unlike desynchronization commonly observed during wakeful movements, beta oscillations (13-35 Hz) synchronized during REM sleep movements; furthermore, high-frequency oscillations (150-350 Hz) synchronized during movement irrespective of sleep-wake states. Our results demonstrate differential engagement of the basal ganglia during REM sleep and awake movements.
Postural analysis reveals persistent vigilance in paper wasps after conspecific challenge
Authors: Legan Andrew W. , Vogt Caleb C. , Sheehan Michael J.
Published: May 2022

Vigilant animals detect and respond to threats in the environment, often changing posture and movement patterns. In social animals vigilance is modulated not only by predators but also by threatening conspecifics. Precisely how social interactions alter vigilance behavior over time is not well understood. We report persistent effects of a simulated social challenge on the vigilance behavior of wild northern paper wasp foundresses,Polistes fuscatus. During the founding phase of the colony cycle conspecific wasps may usurp nests from the resident foundress, representing a severe threat. Using postural tracking, we found that after simulated intrusions wasps displayed increased vigilance during the minutes after the threat was removed. Sustained vigilance elicited after social threat manifested as increased movement, greater bilateral wing extension, and reduced antennal separation. However, no postural changes were observed after a control stimulus presentation. By rapidly adjusting individual vigilance behavior after fending off a conspecific intruder, paper wasp foundresses invest in surveillance of potential social threats, even when such threats are no longer immediately present. The prolonged state of vigilance observed here is relevant to plasticity of recognition processes as a result of conspecific threats.
Nucleotide-decoupled G proteins reveal the role of G protein conformation in receptor-G protein selectivity
Authors: Jang Wonjo , Lu Sumin , Lambert Nevin A.
Published: May 2022

G protein-coupled receptors (GPCRs) selectively activate at least one of the four families of heterotrimeric G proteins to transduce environmental cues, but the mechanistic basis of coupling selectivity remains unclear. Structural studies have emphasized structural complementarity of GPCR complexes with nucleotide-free G proteins, but it has also been suggested that selectivity may be determined by intermediate activation processes that occur prior to nucleotide release. To test these ideas we have studied coupling to nucleotide- decoupled G protein variants, which can adopt conformations similar to receptor-bound G proteins without the need for nucleotide release. We find that selectivity is significantly degraded when nucleotide release is not required for GPCR-G protein complex formation, to the extent that most GPCRs interact with most nucleotide-decoupled G proteins. These findings demonstrate the absence of absolute structural incompatibility between most GPCRs and G proteins, and are consistent with the hypothesis that high-energy intermediate state complexes are involved in coupling selectivity.
Stable High-Concentration Monoclonal Antibody Formulations Enabled by an Amphiphilic Copolymer Excipient
Authors: Klich John H. , Kasse Catherine M. , Mann Joseph L. , Huang Yaoqi , d’Aquino Andrea I. , Grosskopf Abigail K. , Baillet Julie , Fuller Gerald G. , Appel Eric A.
Published: May 2022

Monoclonal antibodies are a staple in modern pharmacotherapy. Unfortunately, these biopharmaceuticals are limited by their tendency to aggregate in formulation, resulting in poor stability and often requiring low concentration drug formulations. Moreover, existing excipients designed to stabilize these formulations are often limited by their toxicity and tendency to form particles such as micelles. Here, we demonstrate the ability of a simple “drop-in”, amphiphilic copolymer excipient to enhance the stability of high concentration formulations of clinically-relevant monoclonal antibodies without altering their pharmacokinetics or injectability. Through interfacial rheology and surface tension measurements, we demonstrate that the copolymer excipient competitively adsorbs to formulation interfaces. Further, through determination of monomeric composition and retained bioactivity through stressed aging, we show that this excipient confers a significant stability benefit to high concentration antibody formulations. Finally, we demonstrate that the excipient behaves as an inactive ingredient, having no significant impact on the pharmacokinetic profile of a clinically relevant antibody in mice. This amphiphilic copolymer excipient demonstrates promise as a simple formulation additive to create stable, high concentration antibody formulations, thereby enabling improved treatment options such as a route-of-administration switch from low concentration intravenous (IV) to high concentration subcutaneous (SC) delivery while reducing dependence on the cold chain.
First Report of Susceptibility Status of the Invasive Vector:Aedes albopictusto insecticides used in vector control in Morocco
Authors: Aboulfadl Souhail , Mellouki Fouad , Ameur Btissam , Faraj Chafika
Published: May 2022

Aedes albopictushas been newly recorded in Agdal district at Rabat in Morocco. The establishment of this invasive mosquito could affect the public health by causing serious epidemics despite of its high nuisance in urban and sub-urban areas. Vector control is mainly based on environmental management but chemical insecticides can be used to reduce adult mosquito densities during peak periods. However, the level of susceptibility of this mosquito to insecticides has not been studied yet in Morocco.

This paper reports the results of the first study conducted to monitor the insecticide resistance of adult and larvaAe. albopictusto the insecticides currently used in the vector control. The study was carried out during May-June 2018 at Rabat from the north-west of the country. Adult susceptibility tests were performed following the WHO test procedures. One organochlorate (DDT 4%), one pyrethroids (cyfluthrin 0.15%), one carbamate (bendiocarb 0.1%) and one organophosphate (fenithrothion 1%) were tested at diagnostic doses (DD). The five-fold DD of bendiocarb were also used to yield information on the intensity of mosquito adult resistance. The results of the performed susceptibility bioassay showed that the vector is susceptible to cyfluthrin and resistant to DDT, bendiocarb and fenithrothion.

Larval bioassays to temephos were conducted according to WHO standard operating protocol to establish the dose-mortality relationship and deduct the LC50 and LC90 then resistance ratios. We show that larval populations ofAe. albopictusare still sensible to this insecticide. This information could help policy-makers to plan insecticide resistance management.
Masked Inverse Folding with Sequence Transfer for Protein Representation Learning
Authors: Yang Kevin K. , Yeh Hugh , Zanichelli Niccolò
Published: May 2022

Abstract

Self-supervised pretraining on protein sequences has led to state-of-the art performance on protein function and fitness prediction. However, sequence-only methods ignore the rich information contained in experimental and predicted protein structures. Meanwhile, inverse folding methods reconstruct a protein’s amino-acid sequence given its structure, but do not take advantage of sequences that do not have known structures. In this study, we train a masked inverse folding protein masked language model parameterized as a structured graph neural network. During pretraining, this model learns to reconstruct corrupted sequences conditioned on the backbone structure. We then show that using the outputs from a pretrained sequence-only protein masked language model as input to the inverse folding model further improves pretraining perplexity. We evaluate both of these models on downstream protein engineering tasks and analyze the effect of using information from experimental or predicted structures on performance.
Clinical characterization of human monkeypox infections in the Democratic Republic of the Congo
Authors: Pittman Phillip R. , Martin James W. , Kingebeni Placide Mbala , Tamfum Jean-Jacques Muyembe , Wan Qingwen , Reynolds Mary G. , Quinn Xiaofei , Norris Sarah , Townsend Michael B. , Satheshkumar Panayampalli S. , Soltis Bryony , Honko Anna , Güereña Fernando B. , Korman Lawrence , Huggins John W.
Published: May 2022

We describe the results of a prospective observational study of the clinical natural history of human monkeypox virus (MPXV) infections at the remote General Reference Hospital of Kole (Kole hospital), the rainforest of the Congo River basin of the Democratic Republic of the Congo (DRC) from March 2007 until August 2011. The research was conducted jointly by the Institute National de Recherche Biomedical (INRB) and the US Army Medical Research Institute of Infectious Diseases (USAMRIID). The Kole hospital was one of the two previous WHO Monkeypox (MPX) study sites (1981-1986). The hospital is staffed by a Spanish Order of Catholic Nuns from La Congregation Des Seours Missionnaires Du Christ Jesus including two Spanish physicians, who were members of the Order as well, were part of the WHO study on human monkeypox. Of 244 patients admitted with a clinical diagnosis of MPXV infection, 216 were positive in both the Pan-Orthopox and MPXV specific PCR. The cardinal observations of these 216 patients are summarized in this report. There were three deaths (3/216) among these hospitalized patients; fetal death occurred in 4 of 5 (80%) patients who were pregnant at admission. The most common complaints were rash (96.8%), malaise (85.2%), sore throat (78.2%), and lymphadenopathy/adenopathy (57.4%). The most common physical exam findings were MPX rash (99.5%) and lymphadenopathy (98.6%). Age group of less than 5 years had the highest lesion count. Primary household cases tended to have higher lesion counts than secondary or later same household cases. Of the 216 patients, 200 were tested for IgM & IgG antibodies (Abs) to Orthopoxviruses. All 200 patients had anti-orthopoxvirus IgG Abs; whereas 189/200 were positive for IgM. Patients with hypoalbuminemia had a high risk of severe disease. Patients with fatal disease had significantly higher maximum geometric mean values than survivors for the following variables, respectively: viral DNA in blood (DNAemia, p=0.0072); maximum lesion count (p=0.0025); day of admission mean AST and ALT (p=0.0002 and p = 0.0224, respectively, adjusted p-values).

Author Summary

This is a prospective observational study of Human monkeypox disease, an emerging infectious disease in parts of the continent of Africa. There are certain differential characteristics when compared to other pox diseases. This paper describes the presenting symptoms and signs of human monkeypox disease, laboratory findings and makes recommendation for the medical treatment of patients with monkeypox disease.
A single-cell atlas of bobtail squid visual and nervous system highlights molecular principles of convergent evolution
Authors: Gavriouchkina Daria , Tan Yongkai , Ziadi-Künzli Fabienne , Hasegawa Yuko , Piovani Laura , Zhang Lin , Sugimoto Chikatoshi , Luscombe Nicholas , Marlétaz Ferdinand , Rokhsar Daniel S.
Published: May 2022

Although the camera-type eyes of cephalopods and vertebrates are a canonical example of convergent morphological evolution, the cellular and molecular mechanisms underlying this convergence remain obscure. We used genomics and single cell transcriptomics to study these mechanisms in the visual system of the bobtail squid Euprymna berryi, an emerging cephalopod model. Analysis of 98,537 cellular transcriptomes from the squid visual and nervous system identified dozens of cell types that cannot be placed in simple correspondence with those of vertebrate or fly visual systems, as proposed by Ramón y Cajal and J.Z. Young. Instead, we find an unexpected diversity of neural types, dominated by dopamine, and previously uncharacterized glial cells. Surprisingly, we observe changes in cell populations and neurotransmitter usage during maturation and growth of the visual systems from hatchling to adult. Together these genomic and cellular findings shed new light on the parallel evolution of visual system complexity in cephalopods and vertebrates.
Computational identification of natural senotherapeutic compounds that mimic dasatinib based on gene expression data
Authors: Meiners Franziska , Secci Riccardo , Sueto Salem , Fuellen Georg , Barrantes Israel
Published: May 2022

The highest risk factor for chronic diseases is chronological age, and age-related chronic diseases account for the majority of deaths worldwide. Targeting senescent cells that accumulate in disease-related tissues presents a strategy to reduce disease burden and to increase healthspan.

Our goal was the computational identification of senotherapeutic repurposing candidates that potentially eliminate senescent cells, based on their similarity in gene expression effects to dasatinib, a tyrosine-kinase inhibitor that induces apoptosis in certain senescent cell types, and that is frequently used as a senolytic together with quercetin.

The natural senolytic piperlongumine (a compound found inlong pepper), and the natural senomorphics parthenolide, phloretin and curcumin (found in various edible plants) were identified as potential substitutes of dasatinib. The gene expression changes underlying the repositioning highlight apoptosis-related genes and pathways. The four compounds, and in particular the top-runner piperlongumine, may be combined with quercetin to obtain natural formulas emulating the dasatinib + quercetin (D+Q) formula that is frequently used in clinical trials targeting senescent cells.
Change point estimation by the mouse medial frontal cortex during probabilistic reward learning
Authors: Murphy Cayla E , Wang Hongli , Ortega Heather K , Kwan Alex C , Atilgan Huriye
Published: May 2022

There are often sudden changes in the state of environment. For a decision maker, accurate prediction and detection of change points are crucial for optimizing performance. Still unclear, however, is whether rodents are simply reactive to reinforcements, or if they can be proactive to estimate future change points during value-based decision making. In this study, we characterize head-fixed mice performing a two-armed bandit task with probabilistic reward reversals. Choice behavior deviates from classic reinforcement learning, but instead suggests a strategy involving belief updating, consistent with the anticipation of change points to exploit the task structure. Excitotoxic lesion and optogenetic inactivation implicate the anterior cingulate and premotor regions of medial frontal cortex. Specifically, over-estimation of hazard rate arises from imbalance across frontal hemispheres during the time window before the choice is made. Collectively, the results demonstrate that mice can capitalize on their knowledge of task regularities, and this estimation of future changes in the environment may be a main computational function of the rodent dorsal medial frontal cortex.
A topography-based predictive framework for naturalistic viewing fMRI
Authors: Li Xuan , Friedrich Patrick , Patil Kaustubh R. , Eickhoff Simon B. , Weis Susanne
Published: May 2022

Recent work has shown great interest in understanding individual differences in complex brain function under naturalistic viewing (NV) conditions. However, methods specifically designed for achieving this goal remain limited. Here, we propose a novel approach, called TOpography-based Predictive Framework (TOPF), to investigate individual differences in evoked brain activity on NV fMRI data. Specifically, TOPF identifies individual-specific evoked activity topographies in a data- driven manner and examines their behavioural relevance using a machine learning predictive framework. Our results show that these topographies successfully predict individual phenotypes across cognition, emotion and personality on unseen subjects, and the identified predictive brain regions are neurobiologically interpretable. Further, the prediction accuracy exceeds that of the commonly-used functional connectivity-based features. Conceptually, we highlight the importance of examining multivariate evoked activity patterns for studying brain-behaviour relationships. In summary, we provide a powerful tool for understanding individual differences and brain-behaviour relationships on NV fMRI data.
An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears
Authors: Lewis Joshua E. , Shebelut Conrad W. , Drumheller Bradley R. , Zhang Xuebao , Shanmugam Nithya , Attieh Michel , Horwath Michael C. , Khanna Anurag , Smith Geoffrey H. , Gutman David A. , Aljudi Ahmed , Cooper Lee A.D. , Jaye David L.
Published: May 2022

Pathologic diagnosis of bone marrow disorders relies in part on microscopic analysis of bone marrow aspirate (BMA) smears and manual counting of marrow nucleated cells to obtain a differential cell count (DCC). This manual process has significant limitations, including analysis of only a small subset of optimal slide areas and nucleated cells, and inter-observer variability due to differences in cell selection and classification. To address these shortcomings, we developed an automated machine learning-based pipeline for obtaining 11-component DCCs on whole-slide BMAs. This pipeline utilizes a sequential process of identifying optimal BMA regions with high proportions of marrow nucleated cells, detecting individual cells within these optimal areas, and classifying these cells into one of 11 DCC components. Convolutional neural network models were trained on 396,048 BMA region, 28,914 cell boundary, and 1,510,976 cell class images from manual annotations. The resulting automated pipeline produces 11-component DCCs that demonstrate high statistical and diagnostic concordance with manual DCCs among a heterogeneous group of testing BMA slides with varying pathologies and cellularities. Additionally, we show that automated analysis can reduce intra-slide variance in DCCs by analyzing the whole slide and marrow nucleated cells within optimal regions. Finally, pipeline outputs of region classification, cell detection, and cell classification can be visualized using whole-slide image analysis software. This study demonstrates the feasibility of a fully-automated pipeline for generating DCCs on scanned whole-slide BMA images, with the potential for improving the current standard of practice for utilizing BMA smears in the laboratory analysis of hematologic disorders.
yEvo: a modular eukaryotic genetics and evolution research experience for high school students
Authors: Taylor M. Bryce , Warwick Alexa R. , Skophammer Ryan , Boyer Josephine M. , Geck Renee C. , Gunkelman Kristin , Walson Margaux , Rowley Paul A. , Dunham Maitreya J.
Published: May 2022

Microbial experimental evolution paired with whole-genome sequencing allows researchers to observe evolutionary processes in real-time. The resources for carrying out and analyzing microbial evolution experiments have become more accessible. It is now possible to expand these studies beyond the research laboratory and into the classroom. We have developed a series of five connected and standards-aligned yeast evolution laboratory modules, called “yEvo,” for high school biology students. The modules have been designed to enable students to take agency in answering open-ended research questions. In Module 1, students evolve the baker’s yeast Saccharomyces cerevisiae to tolerate an over-the-counter antifungal drug, and in subsequent modules, investigate how evolved yeasts adapted to this stressful condition at both the phenotype and genotype levels. Pre- and post-surveys from 72 students at two different schools and one-on-one interviews with students and teachers were used to assess our program goals to iteratively improve these modules over three years. We also measured changes in student conceptions of mutation and evolution, confidence in scientific practices, and interest in STEM and biology careers. Students who participated in our experimental evolution module showed improvements in activity-specific concepts, including the importance of variation in evolution and the random nature of mutation. They additionally reported increased confidence in their ability to design a valid biology experiment. Student experimental data replicated literature findings on mechanisms of clotrimazole resistance and has led to new insights into this phenomenon. This collaborative endeavor will serve as a model for other university researchers and K-16 classrooms interested in engaging in open-ended research questions using yeast as a model system.
A Cross-Modal Autoencoder Framework Learns Holistic Representations of Cardiovascular State
Authors: Radhakrishnan Adityanarayanan , Friedman Sam Freesun , Khurshid Shaan , Ng Kenney , Batra Puneet , Lubitz Steven , Philippakis Anthony , Uhler Caroline
Published: May 2022

A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardio-vascular state. In particular, we use our framework to construct such cross-modal representations from cardiac magnetic resonance images (MRIs), containing structural information, and electrocardiograms (ECGs), containing myoelectric information. We leverage the learned cross-modal representation to (1) improve phenotype prediction from a single, accessible phenotype such as ECGs; (2) enable imputation of hard-to-acquire cardiac MRIs from easy-to-acquire ECGs; and (3) develop a framework for performing genome-wide association studies in an unsupervised manner. Our results provide a framework for integrating distinct diagnostic modalities into a common representation that better characterizes physiologic state.
BioTEA: containerized methods of analysis for microarray-based transcriptomics data
Authors: Visentin Luca , Munaron Luca , Ruffinatti Federico Alessandro
Published: May 2022

Tens of thousands of gene expression data sets describing a variety of model organisms in a many different pathophysiological conditions are currently stored in publicly available databases such as Gene Expression Omnibus (GEO) and ArrayExpress. As microarray technology is giving way to RNA-Seq, it becomes strategic to develop high-level tools of analysis to preserve access to this huge amount of information through the most sophisticated methods of data preparation and processing developed over the years, while ensuring at the same time the reproducibility of the results. To meet this need, here we present bioTEA, a novel software tool that combines the ease of use with the versatility and power of an R/Bioconductor-based differential expression analysis, starting from raw data retrieval and preparation to gene annotation. BioTEA is an R-coded pipeline, wrapped in a Python-based command line interface and containerized with Docker technology. The user can choose among multiple options—including gene filtering, batch effect handling, sample pairing, statistical test type—to adapt the algorithm flow to the structure of the particular data set. All these options are saved in single text file which can be easily shared between different laboratories to deterministically reproduce the results. In addition, a detailed log file provides accurate information about each step of analysis. Overall, these features make bioTEA an invaluable tool for both bioiformaticians and wet-lab biologists interested in transcriptomics.
Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics
Authors: Miao Jiacheng , Guo Hanmin , Song Gefei , Zhao Zijie , Hou Lin , Lu Qiongshi
Published: May 2022

Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of Europeans are known to have substantially reduced predictive accuracy in non-European populations, limiting its clinical utility and raising concerns about health disparities across ancestral populations. Here, we introduce a novel statistical framework named X-Wing to improve predictive performance in ancestrally diverse populations. X-Wing quantifies local genetic correlations for complex traits between populations, employs a novel annotation-dependent estimation procedure to amplify correlated genetic effects between populations, and combines multiple population-specific PRS into a unified score with GWAS summary statistics alone as input. Through extensive benchmarking, we demonstrate that X-Wing pinpoints portable genetic effects and substantially improves PRS performance in non-European populations, showing 18.7%-122.1% gain in predictive R2 compared to state-of-the-art methods based on GWAS summary statistics. Overall, X-Wing addresses critical limitations in existing approaches and may have broad applications in cross-population polygenic prediction.
Localized coevolution between microbial predator and prey alters community-wide gene expression and ecosystem function
Authors: Hogle Shane L , Ruusulehto Liisa , Cairns Johannes , Hultman Jenni , Hiltunen Teppo
Published: May 2022

In dynamic and spatially heterogeneous microbial communities, pairs of locally coevolved species interact between themselves and other species across multiple spatial and temporal scales. We currently do not understand how local pairwise coevolutionary processes scale to influence whole microbial communities and how local coevolutionary processes affect wider species interaction networks. Here we investigate the community-wide functional response to a coevolutionary mismatch between a focal bacterial prey species and its ciliate predator in a synthetic 30 species microbial community over two months. We observed that the coevolved prey had little influence on community structure or carrying capacity in the presence or absence of the coevolved predator. However, community metabolic potential (represented by per-cell ATP concentration) was significantly higher in the presence of both coevolved focal species. This ecosystem-level response was mirrored by community-wide transcriptional shifts that resulted in the differential regulation of nutrient acquisition and surface colonization pathways across multiple species. Our findings suggest that the disruption of localized pairwise coevolution can alter community-wide transcriptional networks, even when the overall ecological response is muted. We propose that these altered expression patterns may be an important signal of future diversification and ecological change.
Spinal Fusion Properties of Mechanically-Reinforced, Osteomodulatory Chitosan Hydrogels
Authors: Darkow Blake T. , Herbert Joseph P. , Messler Mark J. , Grisolano Abigail , Hemmerla August J. , Kimes Austin D. , Lanza Julien , Sun Yisheng , Crim Julia R. , Stensby Derek , Wan Caixia , Moore Don K. , Ulery Bret D.
Published: May 2022

Lower back pain is a considerable medical problem that will impact 80% of the U.S. population at some point in their life. For the most severe cases, surgical repair is necessary and is associated with costs upwards of $10.2 billion annually in the United States. To alleviate back pain, spine fusions are a common treatment in which two or more vertebrae are biologically fused together often through the use of a graft material. Unfortunately, iliac crest bone autograft, the current gold standard graft material, can yield insufficient fusion and is associated with considerable donor site morbidity and pain as well as limited supply. Therefore, new materials need to be developed in order to better coordinate healing and new bone growth in the affected area to reduce unnecessary patient burden. In order to address this issue, the incorporation of allograft and one of two types of cellulose (i.e., 0CNCs and CNFs) into a dual-crosslinked chitosan hydrogel loaded with bioactive calcium phosphate was investigated. Hydrogels were then tested for both their material and biological properties. Specifically, hydrogel swelling ratio, mass loss, ion release profile, compressive strength, in vitro biocompatibility and osteoinduction as well as in vivo biocompatibility, and effectiveness in a spine fusion model were determined. Cellulose and allograft incorporation significantly improved hydrogel compressive strength and biocompatibility and CNFs were found to be a significantly more biocompatible form of cellulose than 0CNCs. Additionally, through the controlled delivery of osteoinductive simple signaling molecules (i.e., calcium and phosphate ions), DCF-loaded CNF/Chitosan hydrogels were able to induce osteoblast-like activity in murine mesenchymal stem cells. When evaluated in vivo, these hydrogels were found to be non-toxic though the subacute phase (14 days). A 6-week rabbit spine fusion found these materials to achieve near complete fusion when assessed radiographically. This research provides considerable support for the utility of our novel material for spine fusion procedures as well as other future bone applications.
Effects of source sample amount on biodiversity surveys of bacteria, fungi, and nematodes in soil ecosystems
Authors: Kageyama Takuya , Toju Hirokazu
Published: May 2022

Bacteria, fungi, and nematodes are major components of soil ecosystems, playing pivotal roles in belowground material cycles and biological community processes. A number of studies have recently uncovered the diversity and community structure of those organisms in various types of soil ecosystems based on DNA metabarcoding (amplicon sequencing). However, because each of the most previous studies examined only one or two of the three organismal groups, it remains an important challenge to reveal the entire picture of soil community structure. We herein examined how we could standardize DNA extraction protocols for simultaneous DNA metabarcoding of bacteria, fungi, and nematodes. Specifically, in an Illumina sequencing analysis of forest and farmland soil samples, we performed DNA extraction at five levels of soil-amount settings (0.5 g, 2 g, 5 g, 10 g, and 20 g). We then found that DNA extraction with the 0.5-g soil setting, which had been applied as default in many commercial DNA extraction kits, could lead to underestimation of α-diversity in nematode community. The detected family-level diversity of nematodes, in particular, increased with increasing soil amounts in DNA extraction. Our analyses also indicated that dissimilarity (β-diversity) of community structure among replicate samples were higher in fungi and nematodes than in bacteria, suggesting difference in basic levels of spatial heterogeneity among the three organismal groups. These findings provide platforms for optimizing DNA metabarcoding protocols commonly applicable to major groups of organisms in soil ecosystems.
Reduced memory precision in older age is associated with functional and structural differences in the angular gyrus
Authors: Korkki S. M. , Richter F. R. , Gellersen H. M. , Simons J. S.
Published: May 2022

Decreased fidelity of mnemonic representations plays a critical role in age-related episodic memory deficits, yet the brain mechanisms underlying such reductions remain unclear. Using functional and structural neuroimaging, we examined how changes in two key nodes of the posterior-medial network, the hippocampus and the angular gyrus, might underpin loss of memory precision in older age. Healthy young and older adults completed a memory task that involved reconstructing object features on a continuous scale. Investigation of BOLD activity during retrieval revealed an age-related reduction in activity reflecting successful recovery of object features in the hippocampus, whereas trial-wise modulation of BOLD signal by graded memory precision was diminished in the angular gyrus. Grey matter volume of the angular gyrus further predicted individual differences in memory precision in older age, beyond likelihood of successful retrieval. These findings provide converging evidence for a role of functional and structural integrity of the angular gyrus in constraining the fidelity of episodic remembering in older age, yielding new insights into parietal contributions to age-related episodic memory decline.
The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit
Authors: Zhuang Qian , Qiao Lei , Xu Lei , Yao Shuxia , Chen Shuaiyu , Zheng Xiaoxiao , Li Jialin , Fu Meina , Li Keshuang , Vatansever Deniz , Ferraro Stefania , Kendrick Keith M. , Becker Benjamin
Published: May 2022

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in the last few decades. However, the pivotal brain nodes and directed casual regulation within this inhibitory circuit in humans remains controversial. Here, we capitalize on recent progress in robust and biologically plausible directed causal modelling (DCM-PEB) and a large fMRI response inhibition dataset (n=218) to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory control circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP) and thalamus (rThal).The entire neural circuit exhibited high intrinsic connectivity and an increasing rIFG inflow and its causal regulation over the rCau and rThal during response inhibition. In addition, sex and behavioral performance influenced the architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model. Together these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.
Spectral flow cytometry reveals metabolic heterogeneity in tissue macrophages
Authors: Heieis Graham A , Patente Thiago A , Tak Tamar , Almeida Luís , Everts Bart
Published: May 2022

Tissue-macrophage populations are constituted by a mosaic of phenotypes, yet new methods are needed to link metabolic status to the range of phenotypes in vivo. We therefore designed a high-dimensional panel for spectral flow cytometry to investigate the heterogeneity of tissue macrophage metabolism at steady-state, and their metabolic adaptation in response to infection. Distinct metabolic profiles were observed between tissue macrophages from different peripheral organs, as well as within populations from a specific site. As such, our data show multiple metabolic states in macrophages corresponding to relative stages of maturity in both the peritoneal cavity and small intestine. Immune perturbation with helminth infection further showed that peritoneal macrophages acquire an overall highly metabolically active profile, whereas responding intestinal macrophages displayed minimal changes in their metabolic phenotype. Thus, we demonstrate that high-dimensional, flow-based analysis is an exciting method to interrogate the metabolic heterogeneity and dynamics of tissue-macrophage populations.
LoRTIS Software Suite: Transposon mutant analysis using long-read sequencing
Authors: Lott Martin , Yasir Muhammad , Turner A. Keith , Bastkowski Sarah , Page Andrew , Webber Mark A. , Charles Ian G.
Published: May 2022

To date transposon insertion sequencing (TIS) methodologies have used short-read nucleotide sequencing technology. However, short-read sequences are unlikely to be matched correctly within repeated genomic regions which are longer than the sequence read. This drawback may be overcome using long-read sequencing technology. We have developed a suite of new analysis tools, the “LoRTIS software suite” (LoRTIS-SS), that produce transposon insertion site mapping data for a reference genome using long-read nucleotide sequence data.

Long-read nucleotide sequence data can be applied to TIS, this enables the unique mapping of transposon insertion sites within long genomic repeated sequences. Here we present long-read TIS analysis software, LoRTIS-SS, which uses the Snakemake framework to manage the workflow. A docker image is provided, complete with dependencies and ten scripts are included for experiment specific data processing before or after use of the main workflow. The workflow uses long-read nucleotide sequence data such as those generated by the MinION sequencer (Oxford Nanopore Technologies). The unique mapping properties of long-read sequence data were exemplified by reference to the ribosomal RNA genes of Escherichia coli strain BW25113, of which there are 7 copies of ∼4.9 kbases in length that are at least 99% similar. Of reads that matched within rRNA genes, approximately half matched uniquely. The software workflow outputs data compatible with the established Bio-TraDIS analysis toolkit allowing for existing workflows to be easily upgraded to support long-read sequencing.