Multiple Sequence Research Articles

Development of RLK-Unet: a clinically favorable deep learning algorithm for brain metastasis detection and treatment response assessment.

Previous deep learning (DL) algorithms for brain metastasis (BM) detection and segmentation have not been commonly used in clinics because they produce false-positive findings, require multiple sequences, and do not reflect physiological properties such as necrosis. The aim of this study was to develop a more clinically favorable DL algorithm (RLK-Unet) using a single sequence reflecting necrosis and apply it to automated treatment response assessment. A total of 128 patients with 1339 BMs, who underwent BM magnetic resonance imaging using the contrast-enhanced 3D T1 weighted (T1WI) turbo spin-echo black blood sequence, were included in the development of the DL algorithm. Fifty-eight patients with 629 BMs were assessed for treatment response. The detection sensitivity, precision, Dice similarity coefficient (DSC), and agreement of treatment response assessments between neuroradiologists and RLK-Unet were assessed. RLK-Unet demonstrated a sensitivity of 86.9% and a precision of 79.6% for BMs and had a DSC of 0.663. Segmentation performance was better in the subgroup with larger BMs (DSC, 0.843). The agreement in the response assessment for BMs between the radiologists and RLK-Unet was excellent (intraclass correlation, 0.84). RLK-Unet yielded accurate detection and segmentation of BM and could assist clinicians in treatment response assessment.

Evolutionary dynamics of the LTR-retrotransposon crapaud in the Podospora anserina species complex and the interaction with repeat-induced point mutations

BackgroundThe genome of the filamentous ascomycete Podospora anserina shows a relatively high abundance of retrotransposons compared to other interspersed repeats. The LTR-retrotransposon family crapaud is particularly abundant in the genome, and consists of multiple diverged sequence variations specifically localized in the 5’ half of both long terminal repeats (LTRs). P. anserina is part of a recently diverged species-complex, which makes the system ideal to classify the crapaud family based on the observed LTR variation and to study the evolutionary dynamics, such as the diversification and bursts of the elements over recent evolutionary time.ResultsWe developed a sequence similarity network approach to classify the crapaud repeats of seven genomes representing the P. anserina species complex into 14 subfamilies. This method does not utilize a consensus sequence, but instead it connects any copies that share enough sequence similarity over a set sequence coverage. Based on phylogenetic analyses, we found that the crapaud repeats likely diversified in the ancestor of the complex and have had activity at different time points for different subfamilies. Furthermore, while we hypothesized that the evolution into multiple subfamilies could have been a direct effect of escaping the genome defense system of repeat induced point mutations, we found this not to be the case.ConclusionsOur study contributes to the development of methods to classify transposable elements in fungi, and also highlights the intricate patterns of retrotransposon evolution over short timescales and under high mutational load caused by nucleotide-altering genome defense.

Secure Genomic String Search with Parallel Homomorphic Encryption

Fully homomorphic encryption (FHE) cryptographic systems enable limitless computations over encrypted data, providing solutions to many of today’s data security problems. While effective FHE platforms can address modern data security concerns in unsecure environments, the extended execution time for these platforms hinders their broader application. This project aims to enhance FHE systems through an efficient parallel framework, specifically building upon the existing torus FHE (TFHE) system chillotti2016faster. The TFHE system was chosen for its superior bootstrapping computations and precise results for countless Boolean gate evaluations, such as AND and XOR. Our first approach was to expand upon the gate operations within the current system, shifting towards algebraic circuits, and using graphics processing units (GPUs) to manage cryptographic operations in parallel. Then, we implemented this GPU-parallel FHE framework into a needed genomic data operation, specifically string search. We utilized popular string distance metrics (hamming distance, edit distance, set maximal matches) to ascertain the disparities between multiple genomic sequences in a secure context with all data and operations occurring under encryption. Our experimental data revealed that our GPU implementation vastly outperforms the former method, providing a 20-fold speedup for any 32-bit Boolean operation and a 14.5-fold increase for multiplications.This paper introduces unique enhancements to existing FHE cryptographic systems using GPUs and additional algorithms to quicken fundamental computations. Looking ahead, the presented framework can be further developed to accommodate more complex, real-world applications.

Identification and Validation of the miR156 Family Involved in Drought Responses and Tolerance in Tea Plants (Camellia sinensis (L.) O. Kuntze).

The microRNA156 (miR156) family, one of the first miRNA families discovered in plants, plays various important roles in plant growth and resistance to various abiotic stresses. Previously, miR156s were shown to respond to drought stress, but miR156s in tea plants (Camellia sinensis (L.) O. Kuntze) have not been comprehensively identified and analyzed. Herein, we identify 47 mature sequences and 28 precursor sequences in tea plants. Our evolutionary analysis and multiple sequence alignment revealed that csn-miR156s were highly conserved during evolution and that the rates of the csn-miR156 members' evolution were different. The precursor sequences formed typical and stable stem-loop structures. The prediction of cis-acting elements in the CsMIR156s promoter region showed that the CsMIR156s had diverse cis-acting elements; of these, 12 CsMIR156s were found to be drought-responsive elements. The results of reverse transcription quantitative PCR (RT-qPCR) testing showed that csn-miR156 family members respond to drought and demonstrate different expression patterns under the conditions of drought stress. This suggests that csn-miR156 family members may be significantly involved in the response of tea plants to drought stress. Csn-miR156f-2-5p knockdown significantly reduced the Fv/Fm value and chlorophyll content and led to the accumulation of more-reactive oxygen species and proline compared with the control. The results of target gene prediction showed that csn-miR156f-2-5p targeted SQUAMOSA promoter binding protein-like (SPL) genes. Further analyses showed that CsSPL14 was targeted by csn-miR156f-2-5p, as confirmed through RT-qPCR, 5' RLM-RACE, and antisense oligonucleotide validation. Our results demonstrate that csn-miR156f-2-5p and CsSPL14 are involved in drought response and represent a new strategy for increasing drought tolerance via the breeding of tea plants.

Chondrus retortus (Gigartinales, Rhodophyta) in Hawai‘i: a taxonomic and biogeographic puzzle

Abstract Members of the genus Chondrus are well-known from temperate and cold waters. Chondrus ocellatus Holmes was reported from Hawai‘i Island (19° N latitude) in 1999 as a new record based on vegetative and tetrasporangial characteristics. The first specimens were collected by Setchell in 1900 in Hilo, HI. The presence of a Chondrus species in the subtropics has been a phycological enigma for over 100 years. We addressed the question of species identity and biogeographic affinities of the Hawaiian Chondrus with fresh cystocarpic material, DNA samples, and phylogenetic analyses. Analysis and comparison of five genes (nuclear: EF2; plastid: psbA, rbcL, and 23S/UPA; mitochondrial: COI) from Hawaiian Chondrus and holotype and topotype material of 10 of the 11 accepted Chondrus species indicate that Hawaiian specimens are C. retortus Matsumoto et Shimada. However, unlike type material, the Hawaiian specimens are commonly pinnulate, vary significantly in secondary medullary filament density, and have mature cystocarps filling the entire medullary space. This study shows the value of using multi-gene loci and comparing multiple sequences of several species to confirm taxonomic conclusions. Our findings suggest that C. retortus may have immigrated via rafting on natural floating material or on ships’ hulls. Solving this old puzzle adds new insight into Hawaiian phytogeography.

Multiple genome sequences of lactic acid bacteria, Carnobacterium divergens and Carnobacterium maltaromaticum strains, isolated from vacuum-packaged lamb meat.

Here, we report the whole-genome sequences of 11 Carnobacterium divergens and 2 Carnobacterium maltaromaticum bacteria isolated from vacuum-packed chill-stored lamb meat in New Zealand. Examination of these lactic acid bacteria (LAB) genomes will improve our knowledge of their potential antimicrobial activities and spoilage mechanisms of importance to the meat industry.

AMWEst, a new thermostable and detergent-tolerant esterase retrieved from the Albian aquifer

A fosmid library was constructed with the metagenomic DNA from the high-temperature sediment-rich water of the Albian aquifer (Algeria). Functional screening of this library was subsequently done looking for genes encoding lipolytic enzymes. We identified a novel gene named AMWEst (1209 base pairs) encoding a protein of 402 amino acids with a predicted molecular weight of 43.44 kDa and conferring esterase activity. AMWEst was successfully overexpressed in the yeast mesophilic host Saccharomyces cerevisiae, and the expression system used proved to be efficient and produced sufficient activity for its biochemical characterization. Multiple sequence alignment indicated that AMWEst contained a conserved pentapeptide motif (Gly120-His121-Ser122-Gln123-Gly124). The optimum pH and temperature of the recombinant esterase AMWEst were 8 and 80 °C, respectively. Additionally, AMWEst showed higher activity towards short carbon substrates and showed maximum activity for p-nitrophenyl hexanoate (C6). Notably, AMWEst has a remarkable thermostability, and the enzyme retains almost maximum activity at 70 °C after incubation for 1 h. Moreover, enzyme activity was enhanced by high concentrations of SDS and Triton X-100 detergents.Key points• A novel thermostable esterase has been retrieved through functional metagenomics• The esterase is detergent-tolerant, which is attractive for some applications• The esterase can be expressed in a yeast mesophilic host to enhance its yield

In silico analysis of crustacean hyperglycemic hormone family G protein-coupled receptor candidates.

Ecdysteroid molting hormone synthesis is directed by a pair of molting glands or Y-organs (YOs), and this synthesis is inhibited by molt-inhibiting hormone (MIH). MIH is a member of the crustacean hyperglycemic hormone (CHH) neuropeptide superfamily, which includes CHH and insect ion transport peptide (ITP). It is hypothesized that the MIH receptor is a Class A (Rhodopsin-like) G protein-coupled receptor (GPCR). The YO of the blackback land crab, Gecarcinus lateralis, expresses 49 Class A GPCRs, three of which (Gl-CHHR-A9, -A10, and -A12) were provisionally assigned as CHH-like receptors. CrusTome, a transcriptome database assembled from 189 crustaceans and 12 ecdysozoan outgroups, was used to deorphanize candidate MIH/CHH GPCRs, relying on sequence homology to three functionally characterized ITP receptors (BNGR-A2, BNGR-A24, and BNGR-A34) in the silk moth, Bombyx mori. Phylogenetic analysis and multiple sequence alignments across major taxonomic groups revealed extensive expansion and diversification of crustacean A2, A24, and A34 receptors, designated CHH Family Receptor Candidates (CFRCs). The A2 clade was divided into three subclades; A24 clade was divided into five subclades; and A34 was divided into six subclades. The subclades were distinguished by conserved motifs in extracellular loop (ECL) 2 and ECL3 in the ligand-binding region. Eleven of the 14 subclades occurred in decapod crustaceans. In G. lateralis, seven CFRC sequences, designated Gl-CFRC-A2α1, -A24α, -A24β1, -A24β2, -A34α2, -A34β1, and -A34β2, were identified; the three A34 sequences corresponded to Gl-GPCR-A12, -A9, and A10, respectively. ECL2 in all the CFRC sequences had a two-stranded β-sheet structure similar to human Class A GPCRs, whereas the ECL2 of decapod CFRC-A34β1/β2 had an additional two-stranded β-sheet. We hypothesize that this second β-sheet on ECL2 plays a role in MIH/CHH binding and activation, which will be investigated further with functional assays.

Identification and Expression Analysis of Suppressors of Cytokine Signaling from Spotted Seabass (Lateolabrax maculatus)

The suppressor of cytokine signaling (SOCS) plays a negative role in the cytokine signaling pathway, preventing excessive signaling from interfering with the metabolic homeostasis of the body. By regulating the Janus kinase-signal transducer and activator of transcription pathway through negative feedback, SOCS have a significant impact on the regulation of both innate and adaptive immunity against pathogens, thus playing a crucial role in the immune response, growth, and development of the body. In this study, the cDNA sequences of SOCS1, 2, 3a, 3b, 4, 5b, 6, 7, 8, 9, and CISH genes of spotted seabass (Lateolabrax maculatus), an important marine economic fish in China, were cloned using RT-PCR, nested PCR, and RACE techniques. Multiple sequence alignment showed that the SOCS family members shared highly conserved functional structural domains, including the SRC homology 2 domain (SH2 domain) and the SOCS-box domain. The phylogenetic analysis showed that SOCS1, 2, 3a, 3b, 8, and CISH belonged to the type II subfamily of SOCS genes, while SOCS4, 5b, 6, 7, and SOCS9 belonged to the type I subfamily. Furthermore, gene organization and syntenic analysis confirmed the phylogenetic analysis and protein annotation of the SOCS gene family in spotted seabass. Constitutive expression of spotted seabass SOCS genes was observed in various tissues of healthy fish, with varying expression levels. Following the lipopolysaccharide and Edwardsiella tarda challenge, the expression profiles of spotted seabass SOCS genes were differently regulated in the gill, head kidney, intestine, and spleen. These findings provide a basis for future research on the functional properties of SOCS genes in spotted seabass.

Chrysin Inhibits Indonesian Serotype Foot-and-Mouth-Disease Virus Replication: Insights from DFT, Molecular Docking and Dynamics Analyses

Chrysin, a predominant compound in Propolis, possesses diverse bioactivities, including antiviral properties. However, its antiviral efficacy against the Indonesian Foot-and-Mouth Disease Virus (FMDV) serotype remains unexplored. This study investigates Chrysin's inhibitory potential against FMDV Indonesian serotype by targeting the 3C Protease (3CP), a vital enzyme for viral replication. Multiple sequence alignment was used to reveal unique characteristics of the Indonesian serotype's 3CP compared to global serotypes. Density Functional Theory (DFT) calculations assessed Chrysin's interaction with 3CP based on electronegativity. Molecular docking and molecular dynamics analyses evaluated Chrysin's inhibitory activity against 3CP, using homology modeling for the Indonesian serotype's 3CP structure. Luteolin, a known FMDV 3CP inhibitor with a similar structure to Chrysin, served as a reference. Results showed distinct 3CP sequences in the Indonesian serotype compared to O serotypes and others. Chrysin exhibited potential electron-donor activity with lower HOMO and LUMO values than Luteolin, but they had similar energy gaps, i.e., 4.016 and 4.044 eV, respectively. Molecular docking indicated similar binding affinities, with Chrysin (-6.365 kcal/mol) and Luteolin (-6.864 kcal/mol) bound to active site residues. Molecular dynamics analysis demonstrated stable 3CP-Chrysin and 3CP-Luteolin complexes, with minor differences in Radius of gyration (Rg) and Root-Mean-Square Fluctuation (RMSF) below 1 Å. From the ligand stability point of view, Chrysin had comparable stability with Luteolin. However, Chrysin formed fewer hydrogen bonds and displayed greater free-binding energy than Luteolin during simulation periods. These findings suggest that Chrysin holds promise as an inhibitor of the Indonesian serotype's FMDV 3C Protease.

Investigating environmental transmission to resolve a Bacillus cereus group outbreak in a neonatal intensive care unit using core genome multilocus sequence typing

BackgroundWe analyzed an outbreak of Bacillus cereus group (Bcg) at a single-center neonatal intensive care unit level IV by conducting comprehensive sampling of both patients and the environment.MethodsBetween 06/2020 and 10/2021, all Bcg isolates identified by both regular colonization screening and additional sampling of the environment were subjected to whole-genome sequencing, followed by in vitro extraction of MLST ST, resistance genes and virulence factors. Using publicly available genome sequences, we defined an ad hoc core genome multilocus sequence typing (cgMLST) scheme comprising 2759 target genes for Bcg typing, which we applied to the detected isolates. We have compared the results with a stable cgMLST that was published in the meantime and completed the investigation with a SNP analysis.ResultsWe analyzed 28 Bcg isolates from patient and environmental samples using MLST and cgMLST. This revealed multiple sequence types, with ST127 being the most common (n = 13). Both cgMLST schemes grouped ten of the 13 ST127 isolates into a cluster, including two invasive isolates from two different patients and several environmental samples. SNP analysis postulated a screen from a ventilation machine as a possible reservoir.ConclusionIn sensitive settings such as neonatal intensive care units, considering the environment in outbreak analyses is crucial, especially when investigating potential transmission routes through shared devices. When dealing with widespread bacteria such as Bcg, high-resolution typing techniques are necessary. In this study, we successfully resolved an outbreak of Bcg infections using a custom cgMLST scheme combined with a SNP analysis.

Color image encryption based on discrete memristor logistic map and DNA encoding

This paper proposes a color image encryption scheme with new features based on two-dimensional discrete memristor logistic map (2D-MLM), Deoxyribonucleic acid (DNA) encoding and multi-wing hyperchaotic systems. Firstly, the discrete memristor map and four-wing hyperchaotic system are used to generate various pseudo-random sequences. Secondly, the original image is processed in blocks, and DNA encoding and operation are performed on the sub-block image using multiple pseudo-random sequences. Finally, combining the pseudo-random sequence to diffuse the sub-block image and DNA decoding, we can get the encrypted image. The scheme generates a one-time key for each image, and uses multiple different sub-keys to increase the key space. The use of diverse pseudo-random sequences for image scrambling effectively avoids the security risks associated with using a single chaotic sequence. The key space of this algorithm reaches 2425, the information entropy of the ciphertext image is 7.9993, the number of pixels change rate (NPCR) and the uniformed average change intensity (UACI) reach 99.6095 % and 33.5089 %, and the inter-pixel correlation is close to zero. The simulation results prove that the proposed algorithm has good security against many potential attacks.

A CD6 homolog of Nile tilapia (Oreochromis niloticus) conserved binding bacteria involved in the regulation of Streptococcus agalactiae induced inflammation

As a lymphocyte-specific surface receptor belonging to the cysteine-rich superfamily of scavenger receptors, CD6 acts as a pattern recognition receptor for microbial components and is involved in the regulation of inflammatory responses. However, the characteristics and functions of CD6 molecules in lower vertebrates represented by teleost fish are unknown. In this study, a CD6 homolog (designated OnCD6) was characterized from Nile tilapia (Oreochromis niloticus), and establishing its role as a PRRs that participates in immune recognition. OnCD6 contains an open reading frame of 1872 bp that encodes a peptide of 623 amino acids, and contains two conserved SR domain. Multiple sequence alignment revealed that OnCD6 shares a relatively high level of identity with those of other species. Transcriptional expression analysis revealed that OnCD6 was constitutively expressed in immunes tissues such as head kidney and thymus. The expression level of OnCD6 in mainly immune tissues were found significantly upregulated after the injection of Streptococcus agalactiae (S. agalactiae). Moreover, OnCD6 protein was located in the head kidney and brain, mainly over the plasma membrane of lymphocytes in these immune tissues. In vitro experiments showed that CD6 extracellular protein bound to and aggregated several Gram-positive and -negative bacterial strains through the recognition of bacterial surface conserved components LPS and LTA etc. In vivo experiments demonstrated that overexpression OnCD6 before S. agalactiae challenge significantly improved tilapia survival, and this was concomitant with reduced bacterial load and pro-inflammatory cytokines (IL-1β and TNF-α). Taken together, our results illustrated the function of CD6 molecular pattern recognition receptors (PRRs) is conserved and plays an important role in antibacterial infection.

Systematic comparison of variant calling pipelines of target genome sequencing cross multiple next-generation sequencers.

Targeted genomic sequencing (TS) greatly benefits precision oncology by rapidly detecting genetic variations with better accuracy and sensitivity owing to its high sequencing depth. Multiple sequencing platforms and variant calling tools are available for TS, making it excruciating for researchers to choose. Therefore, benchmarking study across different platforms and pipelines available for TS is imperative. In this study, we performed a TS of Reference OncoSpan FFPE (HD832) sample enriched by TSO500 panel using four commercially available sequencers, and analyzed the output 50 datasets using five commonly-used bioinformatics pipelines. We systematically investigated the sequencing quality and variant detection sensitivity, expecting to provide optimal recommendations for future research. Four sequencing platforms returned highly concordant results in terms of base quality (Q20 > 94%), sequencing coverage (>97%) and depth (>2000×). Benchmarking revealed good concordance of variant calling across different platforms and pipelines, among which, FASTASeq 300 platform showed the highest sensitivity (100%) and precision (100%) in high-confidence variants calling when analyzed by SNVer and VarScan 2 algorithms. Furthermore, this sequencer demonstrated the shortest sequencing time (∼21h) at the sequencing mode PE150. Through the intersection of 50 datasets generated in this study, we recommended a novel set of variant genes outside the truth set published by HD832, expecting to replenish HD832 for future research on tumor variant diagnosis. Besides, we applied these five tools to another panel (TargetSeq One) for Twist cfDNA Pan-cancer Reference Standard, comprehensive consideration of SNP and InDel sensitivity, SNVer and VarScan 2 performed best among them. Furthermore, SNVer and VarScan 2 also performed best for six cancer cell lines samples regarding SNP and InDel sensitivity. Considering the dissimilarity of variant calls across different pipelines for datasets from the same platform, we recommended an integration of multiple tools to improve variant calling sensitivity and accuracy for the cancer genome. Illumina and GeneMind technologies can be used independently or together by public health laboratories performing tumor TS. SNVer and VarScan 2 perform better regarding variant detection sensitivity for three typical tumor samples. Our study provides a standardized target sequencing resource to benchmark new bioinformatics protocols and sequencing platforms.

Decaging-to-labeling: Development and investigation of quinone methide warhead for protein labeling

Biomolecule labeling in living systems is crucial for understanding biological processes and discovering therapeutic targets. A variety of labeling warheads have been developed for multiple biological applications, including proteomics, bioimaging, sequencing, and drug development. Quinone methides (QMs), a class of highly reactive Michael receptors, have recently emerged as prominent warheads for on-demand biomolecule labeling. Their highly flexible functionality and tunability allow for diverse biological applications, but remain poorly explored at present. In this regard, we designed, synthesized, and evaluated a series of new QM probes with a trifluoromethyl group at the benzyl position and substituents on the aromatic ring to manipulate their chemical properties for biomolecule labeling. The engineered QM warhead efficiently labeled proteins both in vitro and under living cell conditions, with significantly enhanced activity compared to previous QM warheads. We further analyzed the labeling efficacy with the assistance of density functional theory (DFT) calculations, which revealed that the QM generation process, rather than the reactivity of QM, contributes more predominantly to the labeling efficacy. Noteworthy, twelve nucleophilic residues on the BSA were labeled by the probe, including Cys, Asp, Glu, His, Lys, Asn, Gln, Arg, Ser, Thr, Trp and Tyr. Given their high efficiency and tunability, these new QM warheads may hold great promise for a broad range of applications, especially spatiotemporal proteomic profiling for in-depth biological studies.

A target-triggered mimic nucleic acid enzyme enables versatile and sequence-independent biosensing

Simultaneous quantification of multiple microRNAs (miRNAs) is very important because lots of pathologies are associated with abnormal expressions of several miRNAs. In this work, we proposed an enzyme-assisted cleavage of nucleic acids signal amplification (TMNAE enzyme sensing) based method enable simple, highly sensitive and selective multiple miRNAs detection. Two unmodified probes and analyte were assembled into a Y-shaped structure that contains a nicking endonuclease recognition site in the complementary region of the unmodified probe and two side arms complementary to reporter probe. Thus, it enables the loading of a Nicking endonuclease (NEase) on the complementary region of the unmodified probe, localization to a specific locus through hybridization of the side arms with reporter probe, and cleavage thereof. NEase is employed to recycle the process of Y-shaped structure assisted digestion of reporter probe, thus, resulting in a significant fluorescence signal amplification through which one analyte molecule cleaves thousands of reporter probe molecules. We demonstrate the efficiency of this TMNAE enzyme sensing strategy for rapid direct quantification of multiple sequence specific miRNAs in homogeneous solution with the detection limit in the femtomolar range, nearly 4 orders of magnitude lower than that of conventional hybridization assay methods. This assay also has the ability to discriminate the target from other miRNAs or even single-base mismatched sequences. Moreover, the TMNAE enzyme sensing strategy can be used to detect other molecules apart from nucleic acids. The detection of thrombin in biological samples showed a LOD of as low as 1 nM. Overall, our proposed TMNAE enzyme sensing strategy provides a versatile, reliable, simple, highly sensitive, and selective detection method and shows promising application in molecular disease diagnosis and biomedicine.

Genetic consequences of effective and suboptimal dosing with mutagenic drugs in a hamster model of SARS-CoV-2 infection.

Mutagenic antiviral drugs have shown promise against multiple viruses, but concerns have been raised about whether their use might promote the emergence of new and harmful viral variants. Recently, genetic signatures associated with molnupiravir use have been identified in the global SARS-COV-2 population. Here, we examine the consequences of using favipiravir and molnupiravir to treat SARS-CoV-2 infection in a hamster model, comparing viral genome sequence data collected from (1) untreated hamsters, and (2) from hamsters receiving effective and suboptimal doses of treatment. We identify a broadly linear relationship between drug dose and the extent of variation in treated viral populations, with a high proportion of this variation being composed of variants at frequencies of less than 1 per cent, below typical thresholds for variant calling. Treatment with an effective dose of antiviral drug was associated with a gain of between 7 and 10 variants per viral genome relative to drug-free controls: even after a short period of treatment a population founded by a transmitted virus could contain multiple sequence differences to that of the original host. Treatment with a suboptimal dose of drug showed intermediate gains of variants. No dose-dependent signal was identified in the numbers of single-nucleotide variants reaching frequencies in excess of 5 per cent. We did not find evidence to support the emergence of drug resistance or of novel immune phenotypes. Our study suggests that where onward transmission occurs, a short period of treatment with mutagenic drugs may be sufficient to generate a significant increase in the number of viral variants transmitted.

The Complex GH32 Enzyme Orchestra from Priestia megaterium Holds the Key to Better Discriminate Sucrose-6-phosphate Hydrolases from Other β-Fructofuranosidases in Bacteria.

Inulin is widely used as a prebiotic and emerging as a priming compound to counteract plant diseases. We isolated inulin-degrading strains from the lettuce phyllosphere, identified as Bacillus subtilis and Priestia megaterium, species hosting well-known biocontrol organisms. To better understand their varying inulin degradation strategies, three intracellular β-fructofuranosidases from P. megaterium NBRC15308 were characterized after expression in Escherichia coli: a predicted sucrose-6-phosphate (Suc6P) hydrolase (SacAP1, supported by molecular docking), an exofructanase (SacAP2), and an invertase (SacAP3). Based on protein multiple sequence and structure alignments of bacterial glycoside hydrolase family 32 enzymes, we identified conserved residues predicted to be involved in binding phosphorylated (Suc6P hydrolases) or nonphosphorylated substrates (invertases and fructanases). Suc6P hydrolases feature positively charged residues near the structural catalytic pocket (histidine, arginine, or lysine), whereas other β-fructofuranosidases contain tryptophans. This correlates with our phylogenetic tree, grouping all predicted Suc6P hydrolases in a clan associated with genomic regions coding for transporters involved in substrate phosphorylation. These results will help to discriminate between Suc6P hydrolases and other β-fructofuranosidases in future studies and to better understand the interaction of B. subtilis and P. megaterium endophytes with sucrose and/or fructans, sugars naturally present in plants or exogenously applied in the context of defense priming.

AI Can Identify Solar System Instability Billions of Years in Advance

Rare event schemes require an approximation of the probability of the rare event as a function of system state. Finding an appropriate reaction coordinate is typically the most challenging aspect of applying a rare event scheme. Here we develop an artificial intelligence (AI) based reaction coordinate that effectively predicts which of a limited number of simulations of the solar system will go unstable using a convolutional neural network classifier. The performance of the algorithm does not degrade significantly even 3.5 billion years before the instability. We overcome the class imbalance intrinsic to rare event problems using a combination of minority class oversampling, increased minority class weighting, and pulling multiple non-overlapping training sequences from simulations. Our success suggests that AI may provide a promising avenue for developing reaction coordinates without detailed theoretical knowledge of the system.

M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings.

Understanding metal-protein interaction can provide structural and functional insights into cellular processes. As the number of protein sequences increases, developing fast yet precise computational approaches to predict and annotate metal-binding sites becomes imperative. Quick and resource-efficient pre-trained protein language model (pLM) embeddings have successfully predicted binding sites from protein sequences despite not using structural or evolutionary features (multiple sequence alignments). Using residue-level embeddings from the pLMs, we have developed a sequence-based method (M-Ionic) to identify metal-binding proteins and predict residues involved in metal binding. On independent validation of recent proteins, M-Ionic reports an area under the curve (AUROC) of 0.83 (recall = 84.6%) in distinguishing metal binding from non-binding proteins compared to AUROC of 0.74 (recall = 61.8%) of the next best method. In addition to comparable performance to the state-of-the-art method for identifying metal-binding residues (Ca2+, Mg2+, Mn2+, Zn2+), M-Ionic provides binding probabilities for six additional ions (i.e. Cu2+, Po43-, So42-, Fe2+, Fe3+, Co2+). We show that the pLM embedding of a single residue contains sufficient information about its neighbours to predict its binding properties. M-Ionic can be used on your protein of interest using a Google Colab Notebook (https://bit.ly/40FrRbK). The GitHub repository (https://github.com/TeamSundar/m-ionic) contains all code and data.