bluuebunny/crossref_metadata_2025 huggingface dataset:
High prevalence of ArmA-16S rRNA methyltransferase among aminoglycoside-resistant Klebsiella pneumoniae bloodstream isolates
Authors: Isler Burcu , Falconer Caitlin , Vatansever Cansel , Özer Berna , Çınar Güle , Aslan Abdullah Tarık , Forde Brian , Harris Patrick , Şimşek Funda , Tülek Necla , Demirkaya Hamiyet , Menekşe Şirin , Akalin Halis , Balkan İlker İnanç , Aydın Mehtap , Tigen Elif Tükenmez , Demir Safiye Koçulu , Kapmaz Mahir , Keske Şiran , Doğan Özlem , Arabacı Çiğdem , Yağcı Serap , Hazırolan Gülşen , Bakır Veli Oğuzalp , Gönen Mehmet , Saltoğlu Neşe , Azap Alpay , Azap Özlem , Akova Murat , Ergönül Önder , Can Füsun , Paterson David L.
Published: December 2022

Introduction. Aminoglycosides are used for the treatment of carbapenemase-producing

Klebsiella pneumoniae

(CPK) infections. 16S rRNA methyltransferases (RMTs) confer resistance to all aminoglycosides and are often cocarried with NDM.

Hypothesis/Gap Statement. There is a dart of studies looking at the aminoglycoside resistance mechanisms for invasive CPK isolates, particularly in OXA-48 endemic settings.

Aim. We aimed to determine the prevalence of RMTs and their association with beta lactamases and MLSTs amongst aminoglycoside-resistant CPK bloodstream isolates in an OXA-48 endemic setting.

Methodology. CPK isolates (n=181), collected as part of a multicentre cohort study, were tested for amikacin, gentamicin and tobramycin susceptibility using custom-made sensititre plates (GN2XF, Thermo Fisher Scientific). All isolates were previously subjected to whole-genome sequencing. Carbapenemases, RMTs, MLSTs and plasmid incompatibility groups were detected on the assembled genomes.

Results. Of the 181 isolates, 109(60 %) were resistant to all three aminoglycosides, and 96 of 109(88 %) aminoglycoside-resistant isolates carried an RMT (85 ArmA, 10 RmtC, 4 RmtF1; three isolates cocarried ArmA and RmtC). Main clonal types associated with ArmA were ST2096 (49/85, 58 %) and ST14 (24/85, 28 %), harbouring mainly OXA-232 and OXA-48 +NDM, respectively. RmtC was cocarried with NDM (5/10) on ST395, and NDM +OXA-48 or NDM +KPC (4/10) on ST14, ST15 and ST16. All RMT producers also carried CTX-M-15, and the majority cocarried SHV-106, TEM-150 and multiple other antibiotic resistance genes. The majority of the isolates harboured a combination of IncFIB, IncH and IncL/M type plasmids. Non-NDM producing isolates remained susceptible to ceftazidime-avibactam.

Conclusion. Aminoglycoside resistance amongst CPK bloodstream isolates is extremely common and mainly driven by clonal spread of ArmA carried on ST2096 and ST14, associated with OXA-232 and OXA48 +NDM carriage, respectively.
Loss of species richness with land use intensity is explained by a reduction in niche differences
Authors: Godoy Oscar , Granjel Rodrigo R. , van der Plas Fons , Soliveres Santiago , Penone Caterina , Saiz Hugo , Hölzel Norbet , Prati Daniel , Fischer Markus , Allan Eric
Published: December 2022

Increases in land use intensity (LUI) reduce species richness. However, we have a poor understanding of how underlying coexistence mechanisms are altered by land use and whether diversity loss occurs due to changes in plant-plant interactions (competition and facilitation) or in species intrinsic growth rates. We expect that LUI could reduce stabilizing niche differences and the indirect interactions that promote coexistence (e.g., intransitivity), while increasing competitive inequalities between species. To test the importance of these different processes, we use 8-yr time series from 150 grasslands differing in LUI to evaluate the role of direct and indirect interactions in promoting coexistence between 50 plant species. We show that LUI reduces the number of coexisting species mostly by causing a non-linear reduction in niche differences, rather than by enhancing competitive inequalities. However, surprisingly, niche differences remained important in stabilizing coexistence between those species remaining at high LUI. Indirect interactions were generally less important than direct ones, and played a moderate role in promoting coexistence in smaller assemblages of species at intermediate LUI. Our models could accurately reproduce the decline in diversity seen with LUI, indicating that our time series approach captures the important interactions between species. By analyzing land use effects through recent advances in structural stability applied to community ecology we provide a more mechanistic understanding of its effects. Our results highlight the importance of identifying the niche differences that are lost with increasing LUI, to better predict and manage effects of land use on biodiversity.

Significant statement

Human land use is a major threat to grassland biodiversity. Grasslands with high rates of fertilization, grazing and mowing, contain many fewer plant species. Knowing the underlying causes is necessary for a better management of biodiversity. Here we apply ecological theory to spatiotemporal data on changes in plant abundance in managed grasslands in central Europe. We show that the observed decline in diversity can be explained by how interactions among plant species change with increases in land use intensity. In particular, intensive land use removes the stabilizing effect of self-limiting processes that buffer species against extinction as well as limit competitive dominance. Therefore, actions to promote these stabilizing dynamics among interacting species seem key to restore plant diversity.
Detecting remote homolog using structure alignment algorithms and machine learning
Authors: de Sousa Costa Priscila Caroline , Sakamoto Tetsu
Published: December 2022

Remote homolog detection is a classic problem in Bioinformatics. It attempts to identify distantly related proteins sharing a similar structure. Methods that can accurately detect remote homologs benefit protein functional annotation. Recent computational advances in methods predicting the three-dimensional structure of a protein from amino acid sequences allow the massive use of structural data to develop new tools for identifying remote homologs. In this work, we created a discriminative SVM-based method based on structural alignment algorithms (FATCAT, TM-Align, and LovoAlign) to detect whether a protein is a remote homolog with any proteins in the SCOPe database. The final model showed a ROC AUC of 0.9191.
The use of a graph database is a complementary approach to a classical similarity search for identifying commercially available fragment merges
Authors: Wills Stephanie , Sanchez-Garcia Ruben , Roughley Stephen D. , Merritt Andy , Hubbard Roderick E. , Dudgeon Tim , Davidson James , von Delft Frank , Deane Charlotte M.
Published: December 2022

Abstract

Fragment screening using X-ray crystallography can yield rich structural data to help guide the optimization of low-molecular-weight compounds into more potent binders. Fragment merging, whereby substructural motifs from partially overlapping fragments are incorporated into a single larger compound, represents a potentially powerful and efficient approach for increasing potency. Searching commercial catalogues provides one useful way to quickly and cheaply identify follow-up compounds for purchase and further screening, and circumvents the challenge of synthetic accessibility. The Fragment Network is a graph database that provides a novel way to explore the chemical space surrounding fragment hits. We use an iteration of the database containing >120 million catalogue compounds to find fragment merges for four XChem fragment screening campaigns. Retrieved molecules were filtered using a pipeline of 2D and 3D filters and contrasted against a traditional fingerprint-based similarity search. The two search techniques were found to have complementary results, identifying merges in different regions of chemical space. Both techniques were able to identify merges that are predicted to replicate the interactions made by the parent fragments. This work demonstrates the use of the Fragment Network to increase the yield of fragment merges beyond that of a classical catalogue search, thus increasing the likelihood of finding promising follow-up compounds. We present a pipeline that is able to systematically exploit all known fragment hits by performing large-scale enumeration of all possible fragment pairs for merging.
Structure modeling and specificity of peptide-MHC class I interactions using geometric deep learning
Authors: Aronson Alon , Hochner Tanya , Cohen Tomer , Schneidman-Duhovny Dina
Published: December 2022

Major Histocompatibility Complex (MHC) plays a major role in the adaptive immune response by recognizing foreign proteins through binding to their peptides. In humans alone there are several hundred different MHC alleles, where each allele binds a specific subset of peptides. The peptide-MHC complex on a cell surface is identified by a T-cell receptor (TCR) and this binding invokes an immune response. Therefore, predicting the binding specificity of peptide-MHC pairs is necessary for understanding the immune recognition mechanism. Here, we develop an end-to-end novel deep learning model, MHCfold, that consists of structure and specificity prediction modules for simultaneous modeling of peptide-MHC class I (pMHCI) complexes and prediction of their specificity based on their modeled structure. MHCfold produces highly accurate structures of pMHCI complexes with mean Cα RMSD of 0.98Å and 1.50Å for the MHC α chain and the peptide, respectively. The binding specificity is also predicted with high accuracy (mean AUC of 0.94). Furthermore, the structure modeling component is orders of magnitudes faster than state-of-the-art methods (modeling of 100,000 pMHCI pairs in four hours on a standard computer), enabling high-throughput applications for large immunopeptidomics datasets. While peptide-MHC specificity can be accurately predicted from the sequence alone, TCR specificity prediction likely requires modeling of the 3D structures. We anticipate our model can be further used in structure-based prediction of TCR specificity.

MHCfold is available @https://github.com/dina-lab3D/MHCfold
Estimating admixture pedigrees of recent hybrids without a contiguous reference genome
Authors: Garcia-Erill Genís , Hanghøj Kristian , Heller Rasmus , Wiuf Carsten , Albrechtsen Anders
Published: December 2022

The genome of recently admixed individuals or hybrids have characteristic genetic patterns that can be used to learn about their recent admixture history. One of these are patterns of interancestry heterozygosity, which can be inferred from SNP data from either called genotypes or genotype likelihoods, without the need for information on genomic location. This makes them applicable to a wide range of data that are often used in evolutionary and conservation genomic studies, such as low-depth sequencing mapped to scaffolds and reduced representation sequencing. Here we implement maximum likelihood estimation of interancestry heterozygosity patterns using two complementary models. We furthermore developapoh(Admixture Pedigrees Of Hybrids), a software that uses estimates of paired ancestry proportions to detect recently admixed individuals or hybrids, and to find the most compatible recent admixture pedigree. It furthermore calculates several hybrid indices that make it easier to identify and rank possible admixture pedigrees that could give rise to the estimated patterns. We implementedapohboth as a command line tool and as a Graphical User Interface that allows the user to automatically and interactively explore, rank and visualize compatible recent admixture pedigrees, and calculate the different summary indices. We validate the performance of the method using admixed family trios from the 1000 Genomes Project. In addition, we show its applicability on identifying recent hybrids from RAD-seq data of Grant’s gazelle (Nanger grantiandNanger petersii) and whole genome low depth data of waterbuck (Kobus ellipsiprymnus) which shows complex admixture of up to four populations.
Genomic description of critical upstream cannabinoid biosynthesis genes
Authors: Innes Peter A. , Vergara Daniela
Published: December 2022

Cannabinoid production is one of the key attributes of the plantCannabis sativaand the characterization of the genes involved is an essential first step to develop tools for their optimization. We used bioinformatic approaches to annotate and explore variation in the coding genes for critical enzymes comprising the cannabinoid pathway: Olivetol Synthase (OLS), Olivetolic Acid Cyclase (OAC), and Cannabigerolic Acid Synthase (CBGAS), in multipleC. sativagenomes. These upstream genes of the Cannabinoid Oxidocyclase Genes THCAS, CBDAS, and CBCAS generate the necessary precursor molecules to produce the cannabinoids THC and CBD. We found that these genes vary in copy number and confirm that OLS, OAC, CBGAS, and the Cannabinoid Oxidocyclases are on separate chromosomes, while homologs are found in proximity. CBGAS, located on Chromosome X, suggests potential dosage effects in female plants. Except for the Cannabinoid Oxidocyclase genes, the other genes have multiple exons, up to 10 in CBGAS. Through differential exon usage explorations in CBGAS we found evidence for potential regulatory differences. This study provides valuable insight on the genomic identity and variation of cannabinoid biosynthesis genes that will benefit future research on the origin and evolution of this pathway, driver of economic, social, and medicinal value.
Characterization of sperm motility signaling pathway in a gonochoric coral suggests conservation across sexual systems
Authors: Glass Benjamin H. , Ashey Jill , Okongwu Amarachukwu R. , Putnam Hollie M. , Barott Katie L.
Published: December 2022

Many marine invertebrates liberate their gametes into the water column broadcast spawning, where fertilization hinges upon the successful activation of sperm motility. Here, we investigated the molecular mechanisms underpinning sperm motility in the broadcast spawning coralAstrangia poculata. We found that cytosolic alkalinization activates the pH-sensing enzyme soluble adenylyl cyclase (sAC), followed by motility, inA. poculatasperm. In addition, we show for the first time in any cnidarian that sAC activity is required to activate protein kinase A (PKA) in sperm, and that PKA activity is required for the initiation of sperm motility. Ultrastructures ofA. poculatasperm displayed morphological homology to other gonochoric cnidarians, and investigation of cnidarian proteomes revealed that sAC, the central signaling node in the sperm motility pathway, demonstrates broad structural and functional conservation across a diversity of cnidarian species. Ultimately, these results suggest that the role of sAC signaling in sperm motility is conserved between sperm from gonochoric and hermaphroditic corals, which is surprising given their morphological dissimilarities. This study also offers insight into the evolution of the mechanisms controlling metazoan sperm motility.

Summary statement

For broadcast spawning marine invertebrates, the initiation of sperm motility is essential for fertilization. Here, we provide evidence for conservation of a sperm motility pathway across sexual systems in corals.
Not quite lost in translation: Mistranslation alters adaptive landscape topography and the dynamics of evolution
Authors: Schmutzer Michael , Wagner Andreas
Published: December 2022

Mistranslation – the erroneous incorporation of amino acids into nascent proteins – is a source of protein variation that is orders of magnitude more frequent than DNA mutation. Like other sources of nongenetic variation, it can affect adaptive evolution. We study the evolutionary consequences of mistranslation with experimental data on mistranslation rates applied to three empirical adaptive landscapes. We find that mistranslation generally flattens adaptive landscapes by reducing the fitness of high fitness genotypes and increasing that of low fitness genotypes, but it does not affect all genotypes equally. Most importantly, it increases genetic variation available to selection by rendering many neutral DNA mutations non-neutral. Mistranslation also renders some beneficial mutations deleterious and vice versa. It increases the probability of fixation of 3 to 8 percent of beneficial mutations. Even though mistranslation increases the incidence of epistasis, it also allows populations evolving on a rugged landscape to evolve modestly higher fitness. Our observations show that mistranslation is an important source of non-genetic variation that can affect adaptive evolution on fitness landscapes in multiple ways.
A pan-cnidarian microRNA is an ancient biogenesis regulator of stinging cells
Authors: Fridrich Arie , Salinas-Saaverda Miguel , Kozlolvski Itamar , Surm Joachim M , Chrysostomou Eleni , Tripathi Abhinandan M , Frank Uri , Moran Yehu
Published: December 2022

An ancient evolutionary innovation of a novel cell-type, the stinging cell (cnidocyte), appeared >600 million years ago in the phylum Cnidaria (sea anemones, corals, hydroids, and jellyfish). A complex bursting nano-injector of venom, the cnidocyst, is embedded in cnidocytes and enables cnidarians paralyzing prey and predators, contributing to this phylum’s evolutionary success. In this work, we show that post-transcriptional regulation by a pan-cnidarian microRNA, miR-2022, is essential for biogenesis of these cells. By manipulation of miR-2022 levels in a transgenic reporter line of cnidocytes in the sea anemoneNematostella vectensis, followed by transcriptomics, single-cell data analysis, prey paralysis assays, and cell sorting of transgenic cnidocytes, we reveal that miR-2022 enables cnidocyte biogenesis, while exhibiting a conserved expression domain with its targets in cnidocytes of other cnidarian species. Thus, here we reveal one of nature’s most ancient microRNA-regulated processes by studying the functional basis for its conservation.
DNA-protein quasi-mapping for rapid differential gene expression analysis in non-model organisms
Authors: Santiago Kyle Christian L. , Shrestha Anish M.S.
Published: December 2022

Background

Conventional differential gene expression analysis pipelines for non-model organisms require computationally expensive transcriptome assembly. We recently proposed an alternative strategy of directly aligning RNA-seq reads to a protein database, and demonstrated drastic improvements in speed, memory usage, and accuracy in identifying differentially expressed genes.

Result

Here we report a further speed-up by replacing DNA-protein alignment by quasi-mapping, making our pipeline>1000 × faster than assembly-based approach, and still more accurate. We also compare quasi-mapping to other mapping techniques, and show that it is faster but at the cost of sensitivity.

Conclusion

We provide a quick-and-dirty differential gene expression analysis pipeline for non-model organisms without a reference transcriptome, which directly quasi-maps RNA-seq reads to a reference protein database, avoiding computationally expensive transcriptome assembly.
Polo-like kinase 4 (Plk4) potentiatesanoikis-resistance of p53KO mammary epithelial cells by inducing a hybrid EMT phenotype
Authors: Fonseca Irina , Horta Cíntia , Ribeiro Ana Sofia , Sousa Barbara , Marteil Gaëlle , Bettencourt-Dias Mónica , Paredes Joana
Published: December 2022

Polo-like kinase 4 (Plk4), the major regulator of centriole biogenesis, has emerged as a putative therapeutic target in cancer due to its abnormal expression in human carcinomas, leading to centrosome number deregulation, mitotic defects and chromosomal instability. Moreover, Plk4 deregulation promotes tumor growth and metastasis in mouse models and is significantly associated with poor patient prognosis.

Here, we further investigate the role of Plk4 in carcinogenesis and show that its overexpression significantly potentiates resistance to cell death byanoikisof non-tumorigenic p53 knock-out (p53KO) mammary epithelial cells. Importantly, this effect is independent of Plk4’s role in centrosome biogenesis, suggesting that this kinase has additional cellular functions. Interestingly, the Plk4-inducedanoikisresistance is associated with the induction of a stable hybrid epithelial-mesenchymal phenotype and is partially dependent on P-cadherin upregulation. Furthermore, we found that the conditioned media of Plk4-induced p53KO mammary epithelial cells also inducesanoikisresistance of breast cancer cells in a paracrine way, being also partially dependent on soluble P-cadherin secretion.

Our work shows, for the first time, that high expression levels of Plk4 induceanoikisresistance of both mammary epithelial cells with p53KO background, as well as of breast cancer cells exposed to their secretome, which is partially mediated through P-cadherin upregulation. These results reinforce the idea that Plk4, independently of its role in centrosome biogenesis, functions as an oncogene, by impacting the tumor microenvironment to promote malignancy.
Label-free and high-throughput removal of residual undifferentiated cells from iPSC-derived spinal-cord progenitor cells
Authors: Nguyen Tan Dai , Chooi Wai Hon , Jeon Hyungkook , Chen Jiahui , Roxby Daniel Ninio , Zu Yao Jerome Tan , Yi-Pin Lee Cheryl , Ng Shi-Yan , Chew Sing Yian , Han Jongyoon
Published: December 2022

The transplantation of spinal cord progenitor cells (SCPCs) derived from human induced pluripotent stem cells (iPSCs) has beneficial effects on treating spinal cord injury (SCI). However, the presence of residual undifferentiated iPSCs amongst their differentiated progeny poses a high risk as it can develop teratomas or other types of tumors post-transplantation. Despite the need to remove these residual undifferentiated iPSCs, no specific surface markers can identify them for subsequent removal. By profiling the size of SCPCs after a 10-day differentiation process, we found that the large-sized group contains significantly more cells expressing pluripotent markers. In this study, we employed a sized-based, label-free separation using an inertial microfluidic-based device to remove tumor-risk cells. The device can reduce the number of undifferentiated cells from an SCPC population with high throughput (i.e., > 3 million cells per minute) without affecting cell viability and functions. The sorted cells were verified with immunofluorescence staining, flow cytometry analysis, and colony culture assay. We demonstrated the capabilities of our technology to reduce the percentage of OCT4-positive cells. Our technology has great potential for the ‘downstream processing’ of cell manufacturing workflow, ensuring better quality and safety of transplanted cells.
Dashing Growth Curves – a web application for rapid and interactive analysis of microbial growth curves
Authors: Reiter Michael A. , Vorholt Julia A.
Published: December 2022

Background

Recording and analyzing microbial growth is a routine task in the life sciences. Microplate readers that record dozens to hundreds of growth curves simultaneously are increasingly used for this task, raising the demand for their rapid and reliable analysis.

Results

Here, we present Dashing Growth Curves, an interactive web application (http://dashing-growth-curves.ethz.ch/) that enables researchers to quickly visualize and analyze growth curves without coding knowledge and independent of operating system. Growth curves can be fitted with Logistic or Gompertz growth models, or manually by selecting the linear growth phase in a logarithmic plot. Furthermore, Dashing Growth Curves automatically groups replicate samples and generates downloadable plots for extracted growth parameters such as growth rate or lag time.

Conclusions

Dashing Growth Curves is an open-source web application that reduces the time required to analyze microbial growth curves from hours to minutes.
Effect of unequal vaccination coverage and migration on long-term pathogen evolution in a metapopulation
Authors: Walter Alicia , Gandon Sylvain , Lion Sébastien
Published: December 2022

Worldwide inequalities in vaccine availability are expected to affect the spread and spatial distribution of infectious diseases. It is unclear, however, how spatial variation in vaccination coverage can affect the long-term evolution of pathogens. Here we use an analytical model and numerical simulations to analyse the influence of different imperfect vaccines on the potential evolution of pathogen virulence in a two-population model where vaccination coverage varies between populations. We focus on four vaccines, with different modes of action on the life-cycle of a pathogen infecting two host populations coupled by migration. We show that, for vaccines that reduce infection risk or transmissibility, spatial heterogeneity has little effect on pathogen prevalence and host mortality, and no effect on the evolution of pathogen virulence. In contrast, vaccines that reduce pathogen virulence can select for more virulent pathogens and may lead to the coexistence of different pathogen strains, depending on the degree of spatial heterogeneity in the metapopulation. This heterogeneity is driven by two parameters: pathogen migration and the difference in the vaccination rate between the two populations. We show that vaccines that only reduce pathogen virulence select mainly for a single pathogen strategy in the long term while vaccines that reduce both transmission and virulence can favor the coexistence of two pathogen genotypes. We discuss the implications and potential extensions of our analysis.
Varying molecular interactions explain crowder-dependent enzyme function of a viral protease
Authors: Ostrowska Natalia , Feig Michael , Trylska Joanna
Published: December 2022

Biochemical processes in cells, including enzyme-catalyzed reactions, occur in crowded conditions with various background macromolecules occupying up to 40% of cytoplasm’s volume. Viral enzymes in the host cell also encounter such crowded conditions as they often function at the endoplasmic reticulum membranes. We focus on an enzyme encoded by the hepatitis C virus, the NS3/4A protease, which is crucial for viral replication. We have previously found experimentally that synthetic crowders, polyethylene glycol (PEG) and branched polysucrose (Ficoll), differently affect the kinetic parameters of peptide hydrolysis catalyzed by NS3/4A. To gain understanding of the reasons for such behavior, we perform atomistic molecular dynamics simulations of NS3/4A in the presence of either PEG or Ficoll crowders and with and without the peptide substrates. We find that both crowder types make nanosecond long contacts with the protease and slow down its diffusion. However, they also affect the enzyme structural dynamics; crowders induce functionally relevant helical structures in the disordered parts of the protease cofactor, NS4A, with the PEG effect being more pronounced. Overall, PEG interactions with NS3/4A are slightly stronger but Ficoll forms more hydrogen bonds with NS3. The crowders also interact with substrates; we find that the substrate diffusion is reduced much more in the presence of PEG than Ficoll. However, contrary to NS3, the substrate interacts more strongly with Ficoll than with PEG crowders, with the substrate diffusion being similar to crowder diffusion. Importantly, crowders affect also the substrate-enzyme interactions. We observe that both PEG and Ficoll enhance the presence of substrates near the active site, especially near catalytic His57 but Ficoll crowders increase substrate binding more than PEG molecules. The presence of crowders also enhances the stability of Zn2+ion coordination necessary for structural stability of NS3/4A enabling catalysis.

AUTHOR SUMMARY

Enzyme-catalyzed reactions in reality occur in the crowded environment of the cell. Therefore, viruses entering the host cells also encounter a crowded surrounding in which the viral enzymes are replicated. One such enzyme is the NS3/4A protease encoded by the hepatitis C virus. This enzyme is crucial for viral replication and is used as the therapeutic target for clinically approved drugs. To gain understanding of this enzyme function and explain our previous experiments on itsin vitroactivity, we performed atomistic molecular dynamics simulations in the presence of synthetic crowders (polyethylene glycol and polysucrose) mimicking the cellular crowd. Based on these simulations we describe in detail how and why these crowders affect the diffusion and structural dynamics of this enzyme and enzyme-substrate interactions. In fact, crowders enhance substrate binding, which may have vast consequences for its function in the host cell and drug-design.
Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)
Authors: Joodaki Mehdi , Shaigan Mina , Parra Victor , Bülow Roman D. , Kuppe Christoph , Hölscher David L. , Cheng Mingbo , Nagai James S. , Goedertier Michaël , Bouteldja Nassim , Tesar Vladimir , Barratt Jonathan , Roberts Ian S.D. , Coppo Rosanna , Kramann Rafael , Boor Peter , Costa Ivan G.
Published: December 2022

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell and pathomics data to find sample level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics and pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell and pathomics data. Moreover, PILOT provides a statistical approach to delineate non-linear changes in cell populations, gene expression, and tissue structures related to the disease trajectories supporting interpretation of predictions.
Protein Language Model for Prediction of Subcellular Localization of Protein Sequences from Gram-negative bacteria (ProtLM.SCL)
Authors: Singh Gurpreet , Tyagi Ravi , Singh Anjana , Kapil Shruti , Parida Pratap Kumar , Scarcelli Maria , Dumitru Dan , Sathiyamoorthy Nanda Kumar , Phogat Sanjay , Essaghir Ahmed
Published: December 2022

The prediction of bacterial protein Sub-Cellular Localization (SCL) is critical for antigen identification and reverse vaccinology, especially when determining protein localization in the lab is time consuming, expensive and not possible for all species. While PSORTb is one of the most widely used tool for predicting SCL, it has several limitations, including the tendency to label a large number of proteins as ‘Unknown’. To address these shortcomings, we present a protein language model capable of predicting the subcellular localization of a given protein (ProtLM.SCL) from gram-negative bacteria. By performing 10-fold cross validation on the PSORTb public data set, we demonstrate that ProtLM.SCL is more accurate and precise than PSORTb. When compared to empirically validated published data, our models also outperformed PSORTb, particularly when categorizing difficult occurrences.
Adaptive tuning of human learning and choice variability to unexpected uncertainty
Authors: Lee Junseok K. , Rouault Marion , Wyart Valentin
Published: December 2022

Human value-based decisions are strikingly variable under uncertainty. This variability is known to arise from two distinct sources: variable choices aimed at exploring available options, and imprecise learning of option values due to limited cognitive resources. However, whether these two sources of decision variability are tuned to their specific costs and benefits remains unclear. To address this question, we compared the effects of expected and unexpected uncertainty on decision-making in the same reinforcement learning task. Across two large behavioral datasets, we found that humans choose more variably between options but simultaneously learn less imprecisely their values in response to unexpected uncertainty. Using simulations of learning agents, we demonstrate that these opposite adjustments reflect adaptive tuning of exploration and learning precision to the structure of uncertainty. Together, these findings indicate that humans regulate not only how much they explore uncertain options, but also how precisely they learn the values of these options.

Teaser

Humans regulate not only how much they explore uncertain options, but also how precisely they learn their values.
Quantifying constraint in the human mitochondrial genome
Authors: Lake Nicole J. , Liu Wei , Battle Stephanie L. , Laricchia Kristen M. , Tiao Grace , Puiu Daniela , Compton Alison G. , Cowie Shannon , Christodoulou John , Thorburn David R. , Zhao Hongyu , Arking Dan E. , Sunyaev Shamil R. , Lek Monkol
Published: December 2022

Mitochondrial DNA (mtDNA) has an important, yet often overlooked, role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection, representing a powerful tool for identifying genetic variation underlying human phenotypes1–4. However, a constraint model for the mtDNA has not been developed, due to its unique features. Here we describe the development of a mitochondrial constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset reporting mtDNA variation across 56,434 humans5. Our results demonstrate strong depletion of expected variation, suggesting most deleterious mtDNA variants remain undiscovered. To aid their identification, we compute constraint metrics for every mitochondrial protein, tRNA, and rRNA gene, revealing a spectrum of intolerance to variation. We characterize the most constrained regions within genes via regional constraint, and positions across the entire mtDNA via local constraint, showing their enrichment in pathogenic variation and functionally critical sites, including topological clustering in 3D protein and RNA structures. Notably, we identify constraint at often overlooked sites, such as rRNAs and non-coding regions. Lastly, we demonstrate how these metrics can improve the discovery of mtDNA variation underlying rare and common human phenotypes.
ATR inhibition augments the efficacy of lurbinectedin in small cell lung cancer
Authors: Schultz Christopher W. , Zhang Yang , Elmeskini Rajaa , Zimmermann Astrid , Fu Haiqing , Murai Yasuhisa , Wangsa Darawalee , Kumar Suresh , Takahashi Nobuyuki , Atkinson Devon , Saha Liton Kumar , Lee Chien-Fei , Elenbaas Brian , Desai Parth , Sebastian Robin , Ried Thomas , Aladjem Mirit , Zenke Frank T. , Weaver Zoe , Pommier Yves , Thomas Anish
Published: December 2022

Abstract/Summary

Small cell lung cancer (SCLC) is the most lethal type of lung cancer. Specifically, MYC-driven non-neuroendocrine SCLC are particularly resistant to standard therapies. Lurbinectedin was recently approved for the treatment of relapsed SCLC, but combinatorial approaches are needed to increase the depth and duration of responses to lurbinectedin. Using high-throughput screens, we found inhibitors of ataxia telangiectasia–mutated and rad3-related (ATR) as the most effective agents for augmenting lurbinectedin efficacy. First-in-class ATR inhibitor berzosertib synergized with lurbinectedin in multiple SCLC cell lines, organoid andin-vivomodels. Mechanistically, ATR inhibition abrogated S-phase arrest induced by lurbinectedin and forced cell-cycle progression causing mitotic catastrophe and cell death. HighCDKN1A/p21 expression was associated with decreased synergy due to G1 arrest, while increased levels ofERCC5/XPG were predictive of increased combination efficacy. Importantly, MYC-driven non-neuroendocrine tumors which were resistant to first-line therapies displayed decreasedCDKN1A/p21 expression and increasedERCC5/XPG indicating they were primed for response to lurbinectedin-berzosertib combination. The combination is being assessed in a clinical trialNCT04802174.

Graphical Abstract
30×30 biodiversity gains rely on national coordination
Authors: Eckert Isaac , Brown Andrea , Caron Dominique , Riva Federico , Pollock Laura J.
Published: December 2022

Protecting 30% of land by 2030 is an invaluable opportunity to combat the ongoing biodiversity crisis, but critical questions remain regarding what biodiversity to prioritize, how to coordinate protection, and how to incorporate global change. Here, we evaluate how well different 30×30 expansion scenarios capture the climatically viable ranges of Canadian terrestrial vertebrates, plants, and butterflies. We find that national coordination protects vastly more biodiversity (65% of species; 40% of species-at-risk) than regional approaches, which safeguard at least 33% fewer species and 75% fewer species-at-risk. Whereas prioritizing different taxa or biodiversity facets (e.g., phylogenetic diversity) incur smaller trade-offs. Surprisingly, national priorities closely match transnational ones, indicating that national coordination could efficiently contribute to global targets while protecting Canada’s biodiversity at large.
A phylogenetics-based nomenclature system for steroid receptors in teleost fishes
Authors: Hoadley Andrew P. , Munley Kathleen M. , Alward Beau A.
Published: December 2022

Teleost fishes have emerged as tractable models for studying the neuroendocrine regulation of social behavior via molecular genetic techniques, such as CRISPR/Cas9 gene editing. Moreover, teleosts provide an opportunity to investigate the evolution of steroid receptors and their functions, as species within this lineage possess novel steroid receptor paralogs that resulted from a teleost-specific whole genome duplication. Although teleost fishes have grown in popularity as models for behavioral neuroendocrinology, there is not a consistent nomenclature system for steroid receptors and their genes, which may impede a clear understanding of steroid receptor paralogs and their functions. Here, we used a phylogenetic approach to assess the relatedness of protein sequences encoding steroid receptor paralogs in 18 species from 12 different orders of the Infraclass Teleostei. While most similarly named sequences grouped based on the established phylogeny of the teleost fish lineage, our analysis revealed several inconsistencies in the nomenclature of steroid receptor paralogs, particularly for sequences encoding estrogen receptor beta (ERβ). Based on our results, we propose a nomenclature system for teleosts in which Greek symbols refer to proteins and numbers refer to genes encoding different subtypes of steroid receptors within the five major groups of this nuclear receptor subfamily. Collectively, our results bridge a critical gap by providing a cohesive naming system for steroid receptors in teleost fishes, which will serve to improve communication, promote collaboration, and enhance our understanding of the evolution and function of steroid receptors across vertebrates.
Analysis of Gene Expression Heterogeneity Reveals Therapeutic Targets and Novel Regulators of Metastasis
Authors: Yang Dongbo , Dann Christopher , Valdespino Andrea , Robinson-Mailman Lydia , Henn Madeline , Chen Mengje , Balázsi Gábor , Rosner Marsha Rich
Published: December 2022

Tumor cell heterogeneity has been implicated in metastatic progression of solid tumors such as triple-negative breast cancer (TNBC), leading to resistance and recurrence. We hypothesized that genes with low cell-to-cell transcriptional variability may be effective therapeutic targets, and that analysis of variability may facilitate identification of new metastatic regulators. Here we demonstrate, using single cell RNA sequencing, that the metastasis suppressor Raf Kinase Inhibitory Protein (RKIP) reduced overall transcriptional variability in TNBC xenograft tumors. Focusing on genes with reduced variability in response to RKIP, we identified targetable gene sets such as oxidative phosphorylation and showed that metformin could inhibit RKIP-expressing but not control tumor growth. We also found many regulators of cancer progression including a novel epigenetic metastasis suppressor, KMT5C. These studies demonstrate that a metastatic regulator can alter transcriptional variability in tumors and reveal the importance of genes involved in heterogeneity as potential therapeutic targets and regulators of metastatic progression in cancer.
A Potential Pitfall in Detection of Diabetes Mellitus Non-invasively Using the Second-Derivative of Photoplethysmography: Coexisting Hypertension May Blunt the Distinctive Difference in Early Negative to Initial Positive Wave Ratio (b/a) Between People With and Without Diabetes
Authors: Tas Ahmet , Alan Yaren , Kara Ilke , Savas Abdullah , Bayhan Muhammed Ikbal , Ekici Diren , Atay Zeynep , Sezer Fatih , Kitapli Cagla
Published: December 2022

Background

Digital biomarkers have attracted increasing attention as possible non-invasive diagnostic tools for frequent cardiovascular pathologies. Alterations of features extracted from the derivatives and raw signal of photoplethysmography have been found in the presence of cardiovascular risk factors including but not limited to diabetes, hypertension, arterial stiffness, and endothelial dysfunction. In parallel, recent studies have shown promising results regarding the utilization of PPG as a non-invasive diagnostic tool for diabetes. Whether the presence of hypertension impedes the classification due to mutual endothelial insult resulting in peripheral hemodynamic perturbations remains unknown.

Methods

The previously described ratio between the amplitudes of early-negative(b) and initial-positive(a) waves (b/a) was derived from the second derivative of the PPG signal. Patients were classified according to diabetes mellitus type 2 and hypertension. Standard statistical tests were used to compare the means between unpaired subgroups.

Results

Final analysis included 132 patients. Compared to healthy control group DM2(-)HT(-) (-0.263 ± 0.115), both DM2(+)HT(-) (-0.361 ± 0.122, p<0.001,d= 0.83) and HT(+)DM2(-) (-0.319 ± 0.127, p:0.033,d= 0.48) groups had significantly lower b/a values. However, subgroups with one of two conditions had statistically indifferent mean b/a values (DM2(+)HT(-) (-0.361 ± 0.122) vs HT(+)DM2(-) (-0.319 ± 0.127, p:0.212,d:0.32). Moreover, significant difference in b/a between DM2 and non-DM2 subgroups of non-HT group (p<0.001) disappeared in subgroups with HT(p:0.665,d:0.16).

Conclusion

The utilization of the second-derivative of PPG for the detection of diabetes non-invasively may be impeded in patients with cardiovascular comorbidities, especially in the hypertensive population since both HT and DM2 induce parallel b/a ratio alterations due to the mutual undesired perturbations in the cardiovascular system, affecting peripheral flow dynamics.
Leaf gene expression trajectories during the growing season are consistent between sites and years in American beech
Authors: Sezen U. Uzay , Shue Jessica E. , Worthy Samantha J. , Davies Stuart J. , McMahon Sean M. , Swenson Nathan G.
Published: December 2022

Transcriptomics provides a versatile tool for ecological monitoring. Here, through genome-guided profiling of transcripts mapping to 33,042 gene models, expression differences can be discerned among multi-year and seasonal leaf samples collected from American beech trees at two latitudinally separated sites. Despite a bottleneck due to post-Columbian deforestation, the SNP-based population genetic background analysis has yielded sufficient variation to account for differences between populations and among individuals. Our expression analyses during spring-summer and summer-fall transitions for two consecutive years involved 4197 differentially expressed protein coding genes. UsingPopulusorthologs we reconstructed a protein-protein interactome representing leaf physiological states of trees during the seasonal transitions. Gene set enrichment analysis revealed GO terms that highlight molecular functions and biological processes possibly influenced by abiotic forcings such as recovery from drought and response to excess precipitation. Further, based on 324 co-regulated transcripts, we focused on a subset of GO terms that could be putatively attributed to late spring phenological shifts. Our conservative results indicate that extended transcriptome-based monitoring of forests can capture diverse ranges of responses including air quality, chronic disease, as well as herbivore outbreaks that require activation and/or downregulation of genes collectively tuning reaction norms maintaining the survival of long living trees such as the American beech (Fagus grandifolia).
NeuroDecodeR: A package for neural decoding analyses in R
Authors: Meyers Ethan M.
Published: December 2022

Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform decoding analyses in the R programing language. We describe how the package is designed in a modular fashion which allows researchers to easily implement a range of different analyses. We also discuss how to format data to be able to use the package, and we give two examples of how to use the package to analyze real data. We believe that this package, combined with the rich data analysis ecosystem in R, will make it significantly easier for researchers to create reproducible decoding analyses, which should help increase the pace of neuroscience discoveries.
A refined characterization of large-scale genomic differences in the first complete human genome
Authors: Yang Xiangyu , Wang Xuankai , Zou Yawen , Zhang Shilong , Xia Manying , Vollger Mitchell R. , Chen Nae-Chyun , Taylor Dylan J. , Harvey William T. , Logsdon Glennis A. , Meng Dan , Shi Junfeng , McCoy Rajiv C. , Schatz Michael C. , Li Weidong , Eichler Evan E. , Lu Qing , Mao Yafei
Published: December 2022

The first telomere-to-telomere (T2T) human genome assembly (T2T-CHM13) release was a milestone in human genomics. The T2T-CHM13 genome assembly extends our understanding of telomeres, centromeres, segmental duplication, and other complex regions. The current human genome reference (GRCh38) has been widely used in various human genomic studies. However, the large-scale genomic differences between these two important genome assemblies are not characterized in detail yet. Here, we identify 590 discrepant regions (∼226 Mbp) in total. In addition to the previously reported ‘non-syntenic’ regions, we identify 67 additional large-scale discrepant regions and precisely categorize them into four structural types with a newly developed website tool (SynPlotter). The discrepant regions (∼20.4 Mbp) excluding telomeric and centromeric regions are highly structurally polymorphic in humans, where copy number variation are likely associated with various human disease and disease susceptibility, such as immune and neurodevelopmental disorders. The analyses of a newly identified discrepant region—theKLRCgene cluster—shows that the depletion ofKLRC2by a single deletion event is associated with natural killer cell differentiation in ∼20% of humans. Meanwhile, the rapid amino acid replacements within KLRC3 is consistent with the action of natural selection during primate evolution. Our study furthers our understanding of the large-scale structural variation differences between these two crucial human reference genomes and future interpretation of studies of human genetic variation.