Adaptation of Hansenula polymorpha to methanol: a transcriptome analysis

The Biorepository and Integrative Genomics resource for inclusive genomics: insights from a diverse pediatric and admixed cohort

The Biorepository and Integrative Genomics (BIG) Initiative in Tennessee has developed a pioneering resource to address gaps in genomic research by linking genomic, phenotypic, and environmental data from a diverse Mid-South population, including underrepresented groups. We analyzed 13,152 exomes from BIG and found significant genetic diversity, with 50% of participants inferred to have non-European or several types of admixed ancestry. Ancestry within the BIG cohort is stratified, with distinct geographic and demographic patterns, as African ancestry is more common in urban areas, while European ancestry is more common in suburban regions. We observe ancestry-specific rates of novel genetic variants, which are enriched for functional or clinical relevance. Disease prevalence analysis linked ancestry and environmental factors, showing higher odds ratios for asthma and obesity in minority groups, particularly in the urban area. Finally, we observe discrepancies between self-reported race and genetic ancestry, with related individuals self-identifying in differing racial categories. These findings underscore the limitations of race as a biomedical variable. BIG has proven to be an effective model for community-centered precision medicine. We integrated genomics education, and fostered great trust among the contributing communities. Future goals include cohort expansion, and enhanced genomic analysis, to ensure equitable healthcare outcomes.

The abscisic acid signaling negative regulator OsPP2C68 confers drought and salinity tolerance to rice

Clade A type 2 C protein phosphatases (PP2CAs) are core regulatory factors in the plant abscisic acid (ABA) signaling pathway. They play crucial roles in response to abiotic stress. However, a comprehensive understanding of the functions of individual members of rice PP2CA gene families remains limited. This study investigates the role of OsPP2C68 in response to abiotic stress. Our findings indicated that the OsPP2C68 is highly expressed in the embryo and endosperm, and is subcellular localized in the nucleus. OsPP2C68 knockout mutants reduced seed germination and root and stem lengths under ABA treatment. The mutants also exhibited higher stomatal closure rates, indicating increased sensitivity to ABA. In addition, the OsPP2C68 knockout mutants exhibited altered synthesis of osmolytes and antioxidant enzymes under drought and high salinity stress, along with the differential expression of genes associated with drought and salt stress responses, enhancing rice tolerance to drought and salt. These results collectively identify OsPP2C68 as a negative regulator in the rice ABA signaling pathway. It is responsive to drought and salt stress, and involved in regulating stomatal movement.

Adjusted bacterial cooperation in anammox community to adapt to high ammonium in wastewater treatment plant

Bacterial cooperation is very important for anammox bacteria which perform low-carbon and energy-efficient nitrogen removal, yet its variation to adapt to high NH4 +-N concentration in actual wastewater treatment plants (WWTPs) remains unclear. Here, we found wide and varied cross-feedings of anammox bacteria and symbiotic bacteria in the two series connected full-scale reactors with different NH4 +-N concentrations (297.95 ± 54.84 and 76.03 ± 34.01 mg/L) treating sludge digester liquor. The uptake of vitamin B6 as highly effective antioxidants secreted by the symbiotic bacteria was beneficial for anammox bacteria to resist the high NH4 +-N concentration and varied dissolved oxygen (DO). When NH4 +-N concentration in influent (1785.46 ± 228.5 mg/L) increased, anammox bacteria tended to reduce the amino acids supply to symbiotic bacteria to save metabolic costs. A total of 26.1% bacterial generalists switched to specialists to increase the stability and functional heterogeneity of the microbial community at high NH4 +-N conditions. V/A-type ATPase for anammox bacteria to adapt to the change of NH4 +-N was highly important to strive against cellular alkalization caused by free ammonia. This study expands the understanding of the adjusted bacterial cooperation within anammox consortia at high NH4 +-N conditions, providing new insights into bacterial adaptation to adverse environments from a sociomicrobiology perspective.

Ogataea polymorpha as a next-generation chassis for industrial biotechnology

Ogataea (Hansenula) polymorpha is a nonconventional yeast with some unique characteristics, including fast growth, thermostability, and broad substrate spectrum. Other than common applications for protein production, O. polymorpha is attracting interest for chemical and protein production from methanol; a promising feedstock for the next-generation biomanufacturing due to its abundant sources and excellent characteristics. Benefiting from the development of synthetic biology, it has been engineered to produce value-added chemicals by extensively rewiring cellular metabolism. This Review discusses recently developed synthetic biology tools of O. polymorpha. The advances of chemicals production and systems biology were reviewed comprehensively. Finally, we look ahead to the developments of biomanufacturing in O. polymorpha to make an overall understanding of this chassis for academia and industry.

Toden-E: Topology-Based and Density-Based Ensembled Clustering for the Development of Super-PAG in Functional Genomics using PAG Network and LLM

The integrative analysis of gene sets, networks, and pathways is pivotal for deciphering omics data in translational biomedical research. To significantly increase gene coverage and enhance the utility of pathways, annotated gene lists, and gene signatures from diverse sources, we introduced pathways, annotated gene lists, and gene signatures (PAGs) enriched with metadata to represent biological functions. Furthermore, we established PAG-PAG networks by leveraging gene member similarity and gene regulations. However, in practice, high similarity in functional descriptions or gene membership often leads to redundant PAGs, hindering the interpretation from a fuzzy enriched PAG list. In this study, we developed todenE (topology-based and density-based ensemble) clustering, pioneering in integrating topology-based and density-based clustering methods to detect PAG communities leveraging the PAG network and Large Language Models (LLM). In computational genomics annotation, the genes can be grouped/clustered through the gene relationships and gene functions via guilt by association. Similarly, PAGs can be grouped into higher-level clusters, forming concise functional representations called Super-PAGs. TodenE captures PAG-PAG similarity and encapsulates functional information through LLM, in characterizing network-based functional Super-PAGs. In synthetic data, we introduced a metric called the Disparity Index (DI), measuring the connectivity of gene neighbors to gauge clusterability. We compared multiple clustering algorithms to identify the best method for generating performance-driven clusters. In non-simulated data (Gene Ontology), by leveraging transfer learning and LLM, we formed a language-based similarity embedding. TodenE utilizes this embedding together with the topology-based embedding to generate putative Super-PAGs with superior performance in semantic and gene member inclusiveness.

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast could be driven by a number of factors including niche differences or differential access to resistance mutations between species. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants. We found that the distributions of mutational effects displayed by the two species were similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a de novo duplication of the CUP1 gene in S. paradoxus but not in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger effects in S. paradoxus. Our results show that even when available mutations are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

Methods for studying microbial acid stress responses: from molecules to populations

The study of how micro-organisms detect and respond to different stresses has a long history of producing fundamental biological insights while being simultaneously of significance in many applied microbiological fields including infection, food and drink manufacture, and industrial and environmental biotechnology. This is well-illustrated by the large body of work on acid stress. Numerous different methods have been used to understand the impacts of low pH on growth and survival of micro-organisms, ranging from studies of single cells to large and heterogeneous populations, from the molecular or biophysical to the computational, and from well-understood model organisms to poorly defined and complex microbial consortia. Much is to be gained from an increased general awareness of these methods, and so the present review looks at examples of the different methods that have been used to study acid resistance, acid tolerance, and acid stress responses, and the insights they can lead to, as well as some of the problems involved in using them. We hope this will be of interest both within and well beyond the acid stress research community.

Seven quick tips for gene-focused computational pangenomic analysis

Pangenomics is a relatively new scientific field which investigates the union of all the genomes of a clade. The word pan means everything in ancient Greek; the term pangenomics originally regarded genomes of bacteria and was later intended to refer to human genomes as well. Modern bioinformatics offers several tools to analyze pangenomics data, paving the way to an emerging field that we can call computational pangenomics. Current computational power available for the bioinformatics community has made computational pangenomic analyses easy to perform, but this higher accessibility to pangenomics analysis also increases the chances to make mistakes and to produce misleading or inflated results, especially by beginners. To handle this problem, we present here a few quick tips for efficient and correct computational pangenomic analyses with a focus on bacterial pangenomics, by describing common mistakes to avoid and experienced best practices to follow in this field. We believe our recommendations can help the readers perform more robust and sound pangenomic analyses and to generate more reliable results.

Corynebacterium pseudotuberculosis: Whole genome sequencing reveals unforeseen and relevant genetic diversity in this pathogen

Corynebacterium pseudotuberculosis (CPS) is an important bacterial animal pathogen. CPS causes chronic, debilitating and currently incurable infectious diseases affecting a wide range of livestock and wild herbivores including camelids worldwide. Belonging to the Corynebacterium diphtheriae complex, this pathogen can also infect humans. The classical characterization of CPS is typically based on the testing of nitrate reductase activity, separating the two biovars Equi and Ovis. However, more refined resolutions are required to unravel routes of infection. This was realized in our study by generating and analyzing whole genome sequencing (WGS) data. Using newly created core genome multilocus sequence typing (cgMLST) profiles we were the first to discover isolates grouping in a cluster adjacent to clusters formed by CPS biovar Equi isolates. This novel cluster includes CPS isolates from alpacas, llamas, camels and dromedaries, which are characterized by a lack of nitrate reductase activity as encountered in biovar Ovis. This is of special interest for molecular epidemiology. Nevertheless, these isolates bear the genes of the nitrate locus, which are characteristic of biovar Equi isolates. However, sequence analysis of the genes narG and narH of the nitrate locus revealed indels leading to frameshifts and inactivity of the enzymes involved in nitrate reduction. Interestingly, one CPS isolate originating from another lama with an insertion in the MFS transporter (narT) is adjacent to a cluster formed by ovine CPS isolates biovar Equi. Based on this knowledge, the combination of biochemical and PCR based molecular biological nitrate reductase detection can be used for a fast and uncomplicated classification of isolates in routine diagnostics in order to check the origin of camelid CPS isolates. Further analysis revealed that partial sequencing of the ABC transporter substrate binding protein (CP258_RS07935) is a powerful tool to assign the biovars and the novel genomovar.

Dual-Regulation in Peroxisome and Cytoplasm toward Efficient Limonene Biosynthesis with Rhodotorula toruloides

Rhodotorula toruloides is a potential workhorse for production of various value-added chemicals including terpenoids, oleo-chemicals, and enzymes from low-cost feedstocks. However, the limited genetic toolbox is hindering its metabolic engineering. In the present study, four type I and one novel type II peroxisomal targeting signal (PTS1/PTS2) were characterized and employed for limonene production for the first time in R. toruloides. The implant of the biosynthesis pathway into the peroxisome led to 111.5 mg/L limonene in a shake flask culture. The limonene titer was further boosted to 1.05 g/L upon dual-metabolic regulation in the cytoplasm and peroxisome, which included employing the acetoacetyl-CoA synthase NphT7, adding an additional copy of native ATP-dependent citrate lyase, etc. The final yield was 0.053 g/g glucose, which was the highest ever reported. The newly characterized PTSs should contribute to the expansion of genetic toolboxes forR. toruloides. The results demonstrated that R. toruloides could be explored for efficient production of terpenoids.

STED super-resolution microscopy unveils the dynamics of Atg30 on yeast Pex3-labeled peroxisomes

Peroxisomes are dynamic organelles with important metabolic functions. Yeast Pex3 is a multifunctional membrane protein aiding in peroxisomal biogenesis, inheritance, and degradation (pexophagy), by interacting with process-specific factors. Using multicolor (live-cell) stimulated emission depletion (STED) nanoscopy, we studied the localization of Pex3 and its binding partners in Hansenula polymorpha. Unlike confocal microscopy, STED allows resolving the membrane of tiny peroxisomes, enabling accurate measurements of the size of all Pex3-labeled peroxisomes. We localized Pex3 and its binding partners at peroxisome-repressing and -inducing conditions and during pexophagy. In-depth quantitative analysis of Pex3 and pexophagy receptor Atg30 showed dynamic changes in their (co)localization. One remarkable response of Atg30 was the shift in position from being sandwiched between clustered peroxisomes at proliferation conditions, to the cytosolically exposed parts of peroxisome clusters upon pexophagy induction. Summarizing, we show that STED allows characterizing dynamics of the localization of peroxisomal proteins in yeast cells.

Structural basis of human 20S proteasome biogenesis

New proteasomes are produced to accommodate increases in cellular catabolic demand and prevent the accumulation of cytotoxic proteins. Formation of the proteasomal 20S core complex relies on the function of the five chaperones PAC1-4 and POMP. To understand how these chaperones facilitate proteasome assembly, we tagged the endogenous chaperones using CRISPR/Cas gene editing and examined the chaperone-bound complexes by cryo-EM. We observed an early α-ring intermediate subcomplex that is stabilized by PAC1-4, which transitions to β-ring assembly upon dissociation of PAC3/PAC4 and rearrangement of the PAC1 N-terminal tail. Completion of the β-ring and dimerization of half-proteasomes repositions critical lysine K33 to trigger cleavage of the β pro-peptides, leading to the concerted dissociation of POMP and PAC1/PAC2 to yield mature 20S proteasomes. This study reveals structural insights into critical points along the assembly pathway of the human proteasome and provides a molecular blueprint for 20S biogenesis.

Hansenula polymorpha methanol metabolism genes enhance recombinant protein production in Komagataella phaffi

Recombinant protein production in Komagataella phaffi (K. phaffi), a widely utilized host organism, can be optimized by enhancing the metabolic flux in the central carbon metabolism pathways. The methanol utilization pathway (MUT) during methanol-based growth plays a crucial role in providing precursors and energy for cell growth and development. This study investigated the impact of boosting the methanol dissimilation pathway, a branch of MUT that plays a vital role in detoxifying formaldehyde and providing energy in the form of NADH, in K. phaffi. This was achieved by integrating two orthologous genes from Hansenula polymorpha into the K. phaffi genome: formaldehyde dehydrogenase (HpFLD) and formate dehydrogenase (HpFMDH). The HpFLD and HpFMDH genes were isolated from the Hansenula polymorpha genome and inserted under the regulation of the pAOX1 promoter in the genome of recombinant K. phaffi that already contained a single copy of model protein genes (eGFP or EGII). The expression levels of these model proteins were assessed through protein activity assays and gene expression analysis. The findings revealed that while both orthologous genes positively influenced model protein production, HpFMDH exhibited a more pronounced upregulation in expression compared to HpFLD. Co-expression of both orthologous genes demonstrated synergistic effects, resulting in approximately a twofold increase in the levels of the model proteins detected. This study provides valuable insights into enhancing the production capacity of recombinant proteins in K. phaffi.

Glycine rich proteins of ticks: more than a cement component

Glycine-rich proteins (GRPs) are arbitrarily defined as those containing 20% or more glycine residues and constitute a superfamily divided into subfamilies based on their structure and/or function. GRPs have been identified in a diverse array of organisms and have been shown to possess a number of distinctive biological characteristics, including nucleic acid binding, adhesive glue-like properties, antimicrobial activity, involvement in the stress response and in the formation of cuticle components. In ticks, their expression has been described and studied mainly in the salivary glands, and their primary function is usually associated with cement formation and/or structure. Conversely, several GRPs are present in all tick developmental stages, and the expression of many GRP genes is modulated by physiological processes and immune challenges, such as feeding and pathogen infection. Considering that some tick GRPs appear to play essential roles in the tick life cycle, they have been evaluated as immune targets, with a focus on their potential application in vaccine development. This review highlights the roles that tick GRPs may perform beyond the formation and maintenance of the cement scaffold, including structural characterization, locations and functional relevance, hypothetical functions, and their potential use in anti-tick vaccine development.

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus, has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast represents a case of apparent evolutionary constraints favoring greater adaptive capacity in S. cerevisiae. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants isolated from our screen. We found that the distributions of mutational effects displayed by the two species were very similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a single de novo duplication of the CUP1 gene in S. paradoxus but none in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger average effects in S. paradoxus. Our results show that even when the distributions of mutational effects are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

The curses of performing differential expression analysis using single-cell data

Differential expression analysis is pivotal in single-cell transcriptomics for unraveling cell-type- specific responses to stimuli. While numerous methods are available to identify differentially expressed genes in single-cell data, recent evaluations of both single-cell-specific methods and methods adapted from bulk studies have revealed significant shortcomings in performance. In this paper, we dissect the four major challenges in single-cell DE analysis: normalization, excessive zeros, donor effects, and cumulative biases. These "curses" underscore the limitations and conceptual pitfalls in existing workflows. In response, we introduce a novel paradigm addressing several of these issues.

Learning peptide properties with positive examples only

Deep learning can create accurate predictive models by exploiting existing large-scale experimental data, and guide the design of molecules. However, a major barrier is the requirement of both positive and negative examples in the classical supervised learning frameworks. Notably, most peptide databases come with missing information and low number of observations on negative examples, as such sequences are hard to obtain using high-throughput screening methods. To address this challenge, we solely exploit the limited known positive examples in a semi-supervised setting, and discover peptide sequences that are likely to map to certain antimicrobial properties via positive-unlabeled learning (PU). In particular, we use the two learning strategies of adapting base classifier and reliable negative identification to build deep learning models for inferring solubility, hemolysis, binding against SHP-2, and non-fouling activity of peptides, given their sequence. We evaluate the predictive performance of our PU learning method and show that by only using the positive data, it can achieve competitive performance when compared with the classical positive-negative (PN) classification approach, where there is access to both positive and negative examples.

Plant immunity suppression by an β-1,3-glucanase of the maize anthracnose pathogen Colletotrichum graminicola

BACKGROUND

Many phytopathogens secrete a large number of cell wall degrading enzymes (CWDEs) to decompose host cell walls in order to penetrate the host, obtain nutrients and accelerate colonization. There is a wide variety of CWDEs produced by plant pathogens, including glycoside hydrolases (GHs), which determine the virulence, pathogenicity, and host specificity of phytopathogens. The specific molecular mechanisms by which pathogens suppress host immunity remain obscure.

RESULT

In this study, we found that CgEC124 encodes a glycosyl hydrolase with a signal peptide and a conserved Glyco_hydro_cc domain which belongs to glycoside hydrolase 128 family. The expression of CgEC124 was significantly induced in the early stage of Colletotrichum graminicola infection, especially at 12 hpi. Furthermore, CgEC124 positively regulated the pathogenicity, but it did not impact the vegetative growth of mycelia. Ecotopic transient expression of CgEC124 decreased the disease resistance and callose deposition in maize. Moreover, CgEC124 exhibited the β-1,3-glucanase activity and suppresses glucan-induced ROS burst in maize leaves.

CONCLUSIONS

Our results indicate that CgEC124 is required for full virulence of C. graminicola but not for vegetative growth. CgEC124 increases maize susceptibility by inhibiting host reactive oxygen species burst as well as callose deposition. Meanwhile, our data suggests that CgEC124 explores its β-1,3-glucanase activity to prevent induction of host defenses.

miR-26 deficiency causes alterations in lens transcriptome and results in adult-onset cataract

Purpose

Despite strong evidence demonstrating that normal lens development requires regulation governed by miRNAs, the functional role of specific miRNAs in mammalian lens development remains largely unexplored.

Methods

A comprehensive analysis of miRNA transcripts in the newborn mouse lens, exploring both differential expression between lens epithelial cells and lens fiber cells and overall miRNA abundance was conducted by miRNA-seq. Mouse lenses lacking each of three abundantly expressed lens miRNAs: miR-184, miR-26 and miR-1 were analyzed to explore the role of these miRNAs in lens development.

Results

Mice lacking all three copies of miR-26 (miR-26TKO) developed postnatal cataracts as early as 4-6 weeks of age. RNA-seq analysis of neonatal lenses from miR-26TKO mice exhibited abnormal reduced expression of a cohort of genes found to be lens-enriched and linked to cataract (e.g. Foxe3, Hsf4, Mip, Tdrd7, and numerous crystallin genes), and abnormal elevated expression of genes related to neural development (Lhx3, Neurod4, Shisa7, Elavl3 ), inflammation (Ccr1, Tnfrsf12a, Csf2ra), the complement pathway, and epithelial to mesenchymal transition (Tnfrsf1a, Ccl7, Stat3, Cntfr).

Conclusion

miR-1, miR-184 and miR-26 are each dispensable for normal embryonic lens development. However, loss of miR-26 causes lens transcriptome changes and drives cataract formation.

Protein-lipid interactions drive presynaptic assembly upstream of cell adhesion molecules

Textbook models of synaptogenesis position cell adhesion molecules such as neurexin as initiators of synapse assembly. Here we discover a mechanism for presynaptic assembly that occurs prior to neurexin recruitment, while supporting a role for neurexin in synapse maintenance. We find that the cytosolic active zone scaffold SYD-1 interacts with membrane phospholipids to promote active zone protein clustering at the plasma membrane, and subsequently recruits neurexin to stabilize those clusters. Employing molecular dynamics simulations to model intrinsic interactions between SYD-1 and lipid bilayers followed by in vivo tests of these predictions, we find that PIP2-interacting residues in SYD-1's C2 and PDZ domains are redundantly necessary for proper active zone assembly. Finally, we propose that the uncharacterized yet evolutionarily conserved short γ isoform of neurexin represents a minimal neurexin sequence that can stabilize previously assembled presynaptic clusters, potentially a core function of this critical protein.

Automated polyp segmentation based on a multi-distance feature dissimilarity-guided fully convolutional network

Colorectal malignancies often arise from adenomatous polyps, which typically begin as solitary, asymptomatic growths before progressing to malignancy. Colonoscopy is widely recognized as a highly efficacious clinical polyp detection method, offering valuable visual data that facilitates precise identification and subsequent removal of these tumors. Nevertheless, accurately segmenting individual polyps poses a considerable difficulty because polyps exhibit intricate and changeable characteristics, including shape, size, color, quantity and growth context during different stages. The presence of similar contextual structures around polyps significantly hampers the performance of commonly used convolutional neural network (CNN)-based automatic detection models to accurately capture valid polyp features, and these large receptive field CNN models often overlook the details of small polyps, which leads to the occurrence of false detections and missed detections. To tackle these challenges, we introduce a novel approach for automatic polyp segmentation, known as the multi-distance feature dissimilarity-guided fully convolutional network. This approach comprises three essential components, i.e., an encoder-decoder, a multi-distance difference (MDD) module and a hybrid loss (HL) module. Specifically, the MDD module primarily employs a multi-layer feature subtraction (MLFS) strategy to propagate features from the encoder to the decoder, which focuses on extracting information differences between neighboring layers' features at short distances, and both short and long-distance feature differences across layers. Drawing inspiration from pyramids, the MDD module effectively acquires discriminative features from neighboring layers or across layers in a continuous manner, which helps to strengthen feature complementary across different layers. The HL module is responsible for supervising the feature maps extracted at each layer of the network to improve prediction accuracy. Our experimental results on four challenge datasets demonstrate that the proposed approach exhibits superior automatic polyp performance in terms of the six evaluation criteria compared to five current state-of-the-art approaches.

AI in drug discovery and its clinical relevance

The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in the drug discovery pipeline. We present applications of AI at various stages of drug discovery pipelines, including the inherently computational approaches of de novo design and prediction of a drug's likely properties. Open-source databases and AI-based software tools that facilitate drug design are discussed along with their associated problems of molecule representation, data collection, complexity, labeling, and disparities among labels. How contemporary AI methods, such as graph neural networks, reinforcement learning, and generated models, along with structure-based methods, (i.e., molecular dynamics simulations and molecular docking) can contribute to drug discovery applications and analysis of drug responses is also explored. Finally, recent developments and investments in AI-based start-up companies for biotechnology, drug design and their current progress, hopes and promotions are discussed in this article.

Learning Peptide Properties with Positive Examples Only

Deep learning can create accurate predictive models by exploiting existing large-scale experimental data, and guide the design of molecules. However, a major barrier is the requirement of both positive and negative examples in the classical supervised learning frameworks. Notably, most peptide databases come with missing information and low number of observations on negative examples, as such sequences are hard to obtain using high-throughput screening methods. To address this challenge, we solely exploit the limited known positive examples in a semi-supervised setting, and discover peptide sequences that are likely to map to certain antimicrobial properties via positive-unlabeled learning (PU). In particular, we use the two learning strategies of adapting base classifier and reliable negative identification to build deep learning models for inferring solubility, hemolysis, binding against SHP-2, and non-fouling activity of peptides, given their sequence. We evaluate the predictive performance of our PU learning method and show that by only using the positive data, it can achieve competitive performance when compared with the classical positive-negative (PN) classification approach, where there is access to both positive and negative examples.

rCRUX: A Rapid and Versatile Tool for Generating Metabarcoding Reference libraries in R

Key to making accurate taxonomic assignments are curated, comprehensive reference barcode databases. However, the generation and curation of such databases has remained challenging given the large and continuously growing volumes of DNA sequence data and novel reference barcode targets. Monitoring and research applications require a greater diversity of specialized gene regions and targeted taxa to meet taxonomic classification goals then are currently curated by professional staff. Thus, there is a growing need for an easy to implement tool that can generate comprehensive metabarcoding reference libraries for any bespoke locus. We address this need by reimagining CRUX from the Anacapa Toolkit and present the rCRUX package in R. The typical workflow involves searching for plausible seed amplicons (get_seeds_local() or get_seeds_remote()) by simulating in silico PCR to acquire seed sequences containing a user-defined primer set. Next these seeds are used to iteratively blast search seed sequences against a local NCBI formatted database using a taxonomic rank based stratified random sampling approach (blast_seeds()) that results in a comprehensive set of sequence matches. This database is dereplicated and cleaned (derep_and_clean_db()) by identifying identical reference sequences and collapsing the taxonomic path to the lowest taxonomic agreement across all matching reads. This results in a curated, comprehensive database of primer specific reference barcode sequences from NCBI. We demonstrate that rCRUX provides more comprehensive reference databases for the MiFish Universal Teleost 12S, Taberlet trnl, and fungal ITS locus than CRABS, METACURATOR, RESCRIPt, and ECOPCR reference databases. We then further demonstrate the utility of rCRUX by generating 16 reference databases for metabarcoding loci that lack dedicated reference database curation efforts. The rCRUX package provides a simple to use tool for the generation of curated, comprehensive reference databases for user-defined loci, facilitating accurate and effective taxonomic classification of metabarcoding and DNA sequence efforts broadly.

Rheological Dynamics of Active Myxococcus xanthus Populations during Development

The bacterium Myxococcus xanthus produces multicellular droplets called fruiting bodies when starved. These structures form initially through the active dewetting of a vegetative biofilm into surface-associated droplets. This motility-driven aggregation is succeeded by a primitive developmental process in which cells in the droplets mature into nonmotile spores. Here, we use atomic force microscopy to probe the mechanics of these droplets throughout their formation. Using a combination of time- and frequency-domain rheological experiments, we characterize and develop a simple model of the linear viscoelasticity of these aggregates. We then use this model to quantify how cellular behaviors predominant at different developmental times-motility during the dewetting phase and cellular sporulation during later development-manifest as decreased droplet viscosity and increased elasticity, respectively.

Nanozyme can substitute a natural Ogataea polymorpha catalase enzyme in vivo

Nanomaterials possessing artificial, enzyme-like catalytic activity (nanozymes, NZs) have a great potential for application in research, immunological assays, biosensors, in vivo imaging, and as therapeutic agents. Despite the obvious advances in construction and understanding of functional properties of NZs, there is still no clear evidence of whether they can complement the loss of corresponding enzymatic activity in vivo. Herein, we report the first, to the best to our knowledge, example of successful substitution of natural enzyme activity by catalase-like platinum (nPt) and platinum-gold (nPtAu) nanoparticles transferred to the cells of methylotrophic yeast Ogataea polymorpha. The nPt NZs were synthesized by the chemical reduction method and used as a seed to produce the nPt(core)Au(shell) particles. The produced nPt NZs were 68.1 and 91.3 nm in size, while the hydrids were of 531.2 and 615.1 nm. Both nPt and nPtAu demonstrated catalase activity in vitro. The catalase-deficient strain Ogataea polymorpha C-105 was shown to be able to grow on methanol and a mixture of glucose and methanol in the presence although not in the absence of NZs, this correlating with the decrease in intracellular hydrogen peroxide production. The results provide the first example of complementation of the natural enzyme function by synthetic NZs, the phenomenon which can further be used in a screening for new catalase-like nanozymes and as a fruitful tool to modify living cells by nanoparticles possessing catalytic activity and to use such modified cells as sensitive elements in cell-based biosensors.

Discovery of A Polymorphic Gene Fusion via Bottom-Up Chimeric RNA Prediction

Gene fusions and their chimeric products are typically considered hallmarks of cancer. However, recent studies have found chimeric transcripts in non-cancer tissues and cell lines. In addition, efforts to annotate structural variation at large scale have found examples of gene fusions with potential to produce chimeric transcripts in normal tissues. In this report, we provide a means for targeting population-specific chimeric RNAs to enrich for those generated by gene fusion events. We identify 57 such chimeric RNAs from the GTEx cohort, including SUZ12P1-CRLF3 and TFG-ADGRG7 , whose distribution we assessed across the populations of the 1000 Genomes Project. We reveal that SUZ12P1-CRLF3 results from a common complex structural variant in populations with African heritage, and identify its likely mechanism for formation. Additionally, we utilize a large cohort of clinical samples to characterize the SUZ12P1-CRLF3 chimeric RNA, and find an association between the variant and indications of Neurofibramatosis Type I. We present this gene fusion as a case study for identifying hard-to-find and potentially functional structural variants by selecting for those which produce population-specific fusion transcripts.

KEY POINTS

- Discovery of 57 polymorphic chimeric RNAs- Characterization of SUZ12P1-CRLF3 polymorphic chimeric RNA and corresponding rearrangement- Novel bottom-up approach to identify structural variants which produce transcribed gene fusions.

Metabolic engineering of non-conventional yeasts for construction of the advanced producers of biofuels and high-value chemicals

Non-conventional yeasts, i.e. yeasts different from Saccharomyces cerevisiae, represent heterogenous group of unicellular fungi consisting of near 1500 species. Some of these species have interesting and sometimes unique properties like ability to grow on methanol, n-alkanes, ferment pentose sugars xylose and l-arabinose, grow at high temperatures (50°С and more), overproduce riboflavin (vitamin B2) and others. These unique properties are important for development of basic science; moreover, some of them possess also significant applied interest for elaboration of new biotechnologies. Current paper represents review of the recent own results and of those of other authors in the field of non-conventional yeast study for construction of the advanced producers of biofuels (ethanol, isobutanol) from lignocellulosic sugars glucose and xylose or crude glycerol (Ogataea polymorpha, Magnusiomyces magnusii) and vitamin B2 (riboflavin) from glucose and cheese whey (Candida famata).

Plastome characteristics and species identification of Chinese medicinal wintergreens (Gaultheria, Ericaceae)

Wintergreen oil is a folk medicine widely used in foods, pesticides, cosmetics and drugs. In China, nine out of 47 species within Gaultheria (Ericaceae) are traditionally used as Chinese medicinal wintergreens; however, phylogenetic approaches currently used to discriminating these species remain unsatisfactory. In this study, we sequenced and characterized plastomes from nine Chinese wintergreen species and identified candidate DNA barcoding regions for Gaultheria. Each Gaultheria plastome contained 110 unique genes (76 protein-coding, 30 tRNA, and four rRNA genes). Duplication of trnfM, rps14, and rpl23 genes were detected, while all plastomes lacked ycf1 and ycf2 genes. Gaultheria plastomes shared substantially contracted SSC regions that contained only the ndhF gene. Moreover, plastomes of Gaultheria leucocarpa var. yunnanensis contained an inversion in the LSC region and an IR expansion to cover the ndhF gene. Multiple rearrangement events apparently occurred between the Gaultheria plastomes and those from several previously reported families in Ericales. Our phylogenetic reconstruction using 42 plastomes revealed well-supported relationships within all nine Gaultheria species. Additionally, seven mutational hotspot regions were identified as potential DNA barcodes for Chinese medicinal wintergreens. Our study is the first to generate complete plastomes and describe the structural variations of the complicated genus Gaultheria. In addition, our findings provide important resources for identification of Chinese medicinal wintergreens.

Peroxisome biogenesis and inter-organelle communication: an indispensable role for Pex11 and Pex30 family proteins in yeast

Peroxisomes are highly dynamic organelles present in most eukaryotic cells. They also play an important role in human health and the optimum functioning of cells. An extensive repertoire of proteins is associated with the biogenesis and function of these organelles. Two protein families that are involved in regulating peroxisome number in a cell directly or indirectly are Pex11 and Pex30. Interestingly, these proteins are also reported to regulate the contact sites between peroxisomes and other cell organelles such as mitochondria, endoplasmic reticulum and lipid droplets. In this manuscript, we review our current knowledge of the role of these proteins in peroxisome biogenesis in various yeast species. Further, we also discuss in detail the role of these protein families in the regulation of inter-organelle contacts in yeast.

Comparative proteomics analysis of Pichia pastoris cultivating in glucose and methanol

The methylotrophic yeast Pichia pastoris (syn. Komagataella phaffii) has been extensively engineered for protein production, and is attracting attention as a chassis cell for methanol biotransformation toward production of small molecules. However, the relatively unclear methanol metabolism hampers the metabolic rewiring to improve the biosynthetic efficiency. We here performed a label-free quantitative proteomic analysis of Pichia pastoris when cultivated in minimal media containing methanol and glucose, respectively. There were 243, 158 up-regulated proteins and 244, 304 down-regulated proteins in log and stationary phase, respectively, when cultivated in methanol medium compared with that of glucose medium. Peroxisome enrichment further improved the characterization of more differentially expressed proteins (481 proteins in log phase and 524 proteins in stationary phase). We demonstrated the transaldolase isoenzyme (Tal2, Protein ID: C4R244) was highly up-regulated in methanol medium cultivation, which plays an important role in methanol utilization. Our work provides important information for understanding methanol metabolism in methyltrophic yeast and will help to engineer methanol biotransformation in P. pastoris.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

Genome-wide identification and expression analysis of the cucumber PP2C gene family

Background

Type 2C protein phosphatase (PP2C) is a negative regulator of ABA signaling pathway, which plays important roles in stress signal transduction in plants. However, little research on the PP2C genes family of cucumber (Cucumis sativus L.), as an important economic vegetable, has been conducted.

Results

This study conducted a genome-wide investigation of the CsPP2C gene family. Through bioinformatics analysis, 56 CsPP2C genes were identified in cucumber. Based on phylogenetic analysis, the PP2C genes of cucumber and Arabidopsis were divided into 13 groups. Gene structure and conserved motif analysis showed that CsPP2C genes in the same group had similar gene structure and conserved domains. Collinearity analysis showed that segmental duplication events played a key role in the expansion of the cucumber PP2C genes family. In addition, the expression of CsPP2Cs under different abiotic treatments was analyzed by qRT-PCR. The results reveal that CsPP2C family genes showed different expression patterns under ABA, drought, salt, and cold treatment, and that CsPP2C3, 11–17, 23, 45, 54 and 55 responded significantly to the four stresses. By predicting the cis-elements in the promoter, we found that all CsPP2C members contained ABA response elements and drought response elements. Additionally, the expression patterns of CsPP2C genes were specific in different tissues.

Conclusions

The results of this study provide a reference for the genome-wide identification of the PP2C gene family in other species and provide a basis for future studies on the function of PP2C genes in cucumber.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08734-y.

A new approach used in docking study for predicting the combination drug efficacy in EML4-ALK target of NSCLC

Combination drug treatments are usually used in many diseases, including cancers and AIDS. This treatment strategy is known as one of the cornerstone in therapies, which potentially reduces drug toxicity and drug resistance and also enhances therapeutic efficacy. Before using a drug in treatment, several experimental studies are done in vivo and in vitro to ensure the drug's efficacy. In such experimental studies, the drug's efficacy is evaluated with the help of drug dose ratio. In the combination drug experimental studies, the efficacy of the drugs is quantified with the Combination Index (CI) value and then interpreted by various terminologies like synergy, additive, and antagonism. Several computational models have now been invented for the speedy identification of combination drug efficacy. Unfortunately, none of these models have predicted the atomic level interaction of the combination drug with the target protein. This type of intermolecular interaction can be identified with the help of docking software. In the proposed work, we try to identify the intermolecular interaction and efficacy of the combination drug Crzizotinib and Temozolomide in the target of EML4-ALK in NSCLC by in silico study. The result of the study was evaluated with drug properties and Complex Energy (CE) of the docked complex rather than using docking score and binding energy. From this study, we could understand that first, Crizotinib and then after the Temozolomide drug binded on the EML4-ALK protein complex, showed very least CE and also identified that the combination of Crizotinib and Temozolomide drug are more effective in NSCLC.Communicated by Ramaswamy H. Sarma.

Mix and Match: Promoters and Terminators for Tuning Gene Expression in the Methylotrophic Yeast Ogataea polymorpha

The yeast Ogataea polymorpha is an upcoming host for bio-manufacturing due to its unique physiological properties, including its broad substrate spectrum, and particularly its ability to utilize methanol as the sole carbon and energy source. However, metabolic engineering tools for O. polymorpha are still rare. In this study we characterized the influence of 6 promoters and 15 terminators on gene expression throughout batch cultivations with glucose, glycerol, and methanol as carbon sources as well as mixes of these carbon sources. For this characterization, a short half-life Green Fluorescent Protein (GFP) variant was chosen, which allows a precise temporal resolution of gene expression. Our promoter studies revealed how different promoters do not only influence the expression strength but also the timepoint of maximal expression. For example, the expression strength of the catalase promoter (pCAT) and the methanol oxidase promoter (pMOX) are comparable on methanol, but the maximum expression level of the pCAT is reached more than 24 h earlier. By varying the terminators, a 6-fold difference in gene expression was achieved with the MOX terminator boosting gene expression on all carbon sources by around 50% compared to the second-strongest terminator. It was shown that this exceptional increase in gene expression is achieved by the MOX terminator stabilizing the mRNA, which results in an increased transcript level in the cells. We further found that different pairing of promoters and terminators or the expression of a different gene (β-galactosidase gene) did not influence the performance of the genetic parts. Consequently, it is possible to mix and match promoters and terminators as independent elements to tune gene expression in O. polymorpha.

Comparative transcriptome and metabolome analyses reveal the methanol dissimilation pathway of Pichia pastoris

BACKGROUND

Pichia pastoris (Komagataella phaffii) is a model organism widely used for the recombinant expression of eukaryotic proteins, and it can metabolize methanol as its sole carbon and energy source. Methanol is oxidized to formaldehyde by alcohol oxidase (AOX). In the dissimilation pathway, formaldehyde is oxidized to CO2 by formaldehyde dehydrogenase (FLD), S-hydroxymethyl glutathione hydrolase (FGH) and formate dehydrogenase (FDH).

RESULTS

The transcriptome and metabolome of P. pastoris were determined under methanol cultivation when its dissimilation pathway cut off. Firstly, Δfld and Δfgh were significantly different compared to the wild type (GS115), with a 60.98% and 23.66% reduction in biomass, respectively. The differential metabolites between GS115 and Δfld were mainly enriched in ABC transporters, amino acid biosynthesis, and protein digestion and absorption. Secondly, comparative transcriptome between knockout and wild type strains showed that oxidative phosphorylation, glycolysis and the TCA cycle were downregulated, while alcohol metabolism, proteasomes, autophagy and peroxisomes were upregulated. Interestingly, the down-regulation of the oxidative phosphorylation pathway was positively correlated with the gene order of dissimilation pathway knockdown. In addition, there were significant differences in amino acid metabolism and glutathione redox cycling that raised our concerns about formaldehyde sorption in cells.

CONCLUSIONS

This is the first time that integrity of dissimilation pathway analysis based on transcriptomics and metabolomics was carried out in Pichia pastoris. The blockage of dissimilation pathway significantly down-regulates the level of oxidative phosphorylation and weakens the methanol assimilation pathway to the point where deficiencies in energy supply and carbon fixation result in inefficient biomass accumulation and genetic replication. In addition, transcriptional upregulation of the proteasome and autophagy may be a stress response to resolve formaldehyde-induced DNA-protein crosslinking.

Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat (Triticum aestivum L.) Accessions

Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.

Mitochondrial phylogenomics and mitogenome organization in the parasitoid wasp family Braconidae (Hymenoptera: Ichneumonoidea)

BACKGROUND

Mitochondrial (mt) nucleotide sequence data has been by far the most common tool employed to investigate evolutionary relationships. While often considered to be more useful for shallow evolutionary scales, mt genomes have been increasingly shown also to contain valuable phylogenetic information about deep relationships. Further, mt genome organization provides another important source of phylogenetic information and gene reorganizations which are known to be relatively frequent within the insect order Hymenoptera. Here we used a dense taxon sampling comprising 148 mt genomes (132 newly generated) collectively representing members of most of the currently recognised subfamilies of the parasitoid wasp family Braconidae, which is one of the largest radiations of hymenopterans. We employed this data to investigate the evolutionary relationships within the family and to assess the phylogenetic informativeness of previously known and newly discovered mt gene rearrangements.

RESULTS

Most subfamilial relationships and their composition obtained were similar to those recovered in a previous phylogenomic study, such as the restoration of Trachypetinae and the recognition of Apozyginae and Proteropinae as valid braconid subfamilies. We confirmed and detected phylogenetic signal in previously known as well as novel mt gene rearrangements, including mt rearrangements within the cyclostome subfamilies Doryctinae and Rogadinae.

CONCLUSIONS

Our results showed that both the mt genome DNA sequence data and gene organization contain valuable phylogenetic signal to elucidate the evolution within Braconidae at different taxonomic levels. This study serves as a basis for further investigation of mt gene rearrangements at different taxonomic scales within the family.

Characterization of differential gene expression of broiler chicken to thermal stress in discrete developmental stages

Prolonged exposure to high temperatures is linked to a range of physiological responses in broiler chickens including reduced disease resistance, low growth rate, and high mortality rate. In this study, we investigated the effect of heat stress on gene expression levels in 4-week-old and 6-week-old chickens each exposed to environments conditioned at thermoneutral (21 °C) and high (32 °C) temperatures. The analysis of differentially expressed genes (DEGs) using microarray revealed that genes underlying reactive oxygen species (ROS) production, cell nutrient intake, glucose metabolism, and circadian rhythm were differentially regulated in association with heat stress. We also found that the deviation in expression levels across the transcriptome in response to heat stress was significantly stronger (P< 2.2×10-16) in 6-week-olds compared to younger chickens. We finally observed a significant trend (r = 0.78, P< 2.2×10-16) that genes with a higher estimate of expression in the microarray were more likely to have a higher expression level in RNA-sequencing. Together, our findings provide comprehensive insights into the physiology involved in stress responses at varying developmental stages, which may facilitate chicken breeding to maximize their productivity under adverse conditions.

Response mechanisms of Saccharomyces cerevisiae to the stress factors present in lignocellulose hydrolysate and strategies for constructing robust strains

Bioconversion of lignocellulosic biomass to biofuels such as bioethanol and high value-added products has attracted great interest in recent decades due to the carbon neutral nature of biomass feedstock. However, there are still many key technical difficulties for the industrial application of biomass bioconversion processes. One of the challenges associated with the microorganism Saccharomyces cerevisiae that is usually used for bioethanol production refers to the inhibition of the yeast by various stress factors. These inhibitive effects seriously restrict the growth and fermentation performance of the strains, resulting in reduced bioethanol production efficiency. Therefore, improving the stress response ability of the strains is of great significance for industrial production of bioethanol. In this article, the response mechanisms of S. cerevisiae to various hydrolysate-derived stress factors including organic acids, furan aldehydes, and phenolic compounds have been reviewed. Organic acids mainly stimulate cells to induce intracellular acidification, furan aldehydes mainly break the intracellular redox balance, and phenolic compounds have a greater effect on membrane homeostasis. These damages lead to inadequate intracellular energy supply and dysregulation of transcription and translation processes, and then activate a series of stress responses. The regulation mechanisms of S. cerevisiae in response to these stress factors are discussed with regard to the cell wall/membrane, energy, amino acids, transcriptional and translational, and redox regulation. The reported key target genes and transcription factors that contribute to the improvement of the strain performance are summarized. Furthermore, the genetic engineering strategies of constructing multilevel defense and eliminating stress effects are discussed in order to provide technical strategies for robust strain construction. It is recommended that robust S. cerevisiae can be constructed with the intervention of metabolic regulation based on the specific stress responses. Rational design with multilevel gene control and intensification of key enzymes can provide good strategies for construction of robust strains.

Network analysis of atherosclerotic genes elucidates druggable targets

Background

Atherosclerosis is one of the major causes of cardiovascular disease. It is characterized by the accumulation of atherosclerotic plaque in arteries under the influence of inflammatory responses, proliferation of smooth muscle cell, accumulation of modified low density lipoprotein. The pathophysiology of atherosclerosis involves the interplay of a number of genes and metabolic pathways. In traditional translation method, only a limited number of genes and pathways can be studied at once. However, the new paradigm of network medicine can be explored to study the interaction of a large array of genes and their functional partners and their connections with the concerned disease pathogenesis. Thus, in our study we employed a branch of network medicine, gene network analysis as a tool to identify the most crucial genes and the miRNAs that regulate these genes at the post transcriptional level responsible for pathogenesis of atherosclerosis.

Result

From NCBI database 988 atherosclerotic genes were retrieved. The protein–protein interaction using STRING database resulted in 22,693 PPI interactions among 872 nodes (genes) at different confidence score. The cluster analysis of the 872 genes using MCODE, a plug-in of Cytoscape software revealed a total of 18 clusters, the topological parameter and gene ontology analysis facilitated in the selection of four influential genes viz., AGT, LPL, ITGB2, IRS1 from cluster 3. Further, the miRNAs (miR-26, miR-27, and miR-29 families) targeting these genes were obtained by employing MIENTURNET webtool.

Conclusion

Gene network analysis assisted in filtering out the 4 probable influential genes and 3 miRNA families in the pathogenesis of atherosclerosis. These genes, miRNAs can be targeted to restrict the occurrence of atherosclerosis. Given the importance of atherosclerosis, any approach in the understanding the genes involved in its pathogenesis can substantially enhance the health care system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01195-y.

Allelically and Differentially Expressed Genes After Infection of Edwardsiella ictaluri in Channel Catfish as Determined by Bulk Segregant RNA-Seq

Identification of genetic markers associated with resistance against enteric septicemia of catfish (ESC) is of great interest for genetic enhancement programs of catfish. In the present study, bulk segregant RNA-Seq analysis was applied to determine differentially expressed genes and alleles after ESC infection. Here we report three genomic regions on LG1, LG12, and LG26, containing significant single-nucleotide polymorphisms (SNPs). These genomic regions aligned well with quantitative trait loci (QTL) previously identified. Within the QTL regions, eleven genes were found to be differentially regulated between phenotypic bulks. Importantly, the QTL on linkage group 1 (LG1) were found to be expressed in the liver, whereas the QTL on LG12 and LG26 were expressed in the intestine, suggesting multiple mechanisms of ESC resistance. It is apparent that apolipoproteins may be important for ESC resistance as the QTL on LG1 included the 14-kDa apolipoprotein genes that are both allelically expressed and differentially expressed between the resistant and susceptible bulks. Traf2 and NCK-interacting protein kinase (TNIK) were found in the QTL on LG12, and it was downregulated in resistant fish, suggesting the importance of NCK downregulation in ESC resistance, as previously reported. In addition, we observed divergent gene expression patterns between the liver and intestine after infection. Immune/inflammatory-related processes were overrepresented from liver DEGs, while those DEGs identified from intestine were enriched for proteolysis and wounding processes. Taken together, the BSR-Seq analysis presented here advanced the knowledge of ESC resistance, providing information of not only positions of QTL but also genes and their differential expression between resistant and susceptible fish, making it one step closer to the identification of the causal genes for ESC resistance.

Genome-wide identification and expression analysis of the cucumber PYL gene family

Abscisic acid (ABA) is a very important hormone in plants. It regulates growth and development of plants and plays an important role in biotic and abiotic stresses. The Pyrabactin resistance 1-like (PYR/PYL) proteins play a central role in ABA signal transduction pathways. The working system of PYL genes in cucumber, an important economical vegetable (Cucumis sativus L.), has not been fully studied yet. Through bioinformatics, a total of 14 individual PYL genes were identified in Chinese long '9930' cucumber. Fourteen PYL genes were distributed on six chromosomes of cucumber, and their encoded proteins predicted to be distributed in cytoplasm and nucleus. Based on the phylogenetic analysis, the PYL genes of cucumber, Arabidopsis, rice, apple, Brachypodium distachyon and soybeancould be classified into three groups. Genetic structures and conserved domains analysis revealed that CsPYL genes in the same group have similar exons and conserved domains. By predicting cis-elements in the promoters, we found that all CsPYL members contained hormone and stress-related elements. Additionally, the expression patterns of CsPYL genes were specific in tissues. Finally, we further examined the expression of 14 CsPYL genes under ABA, PEG, salt stress. The qRT-PCR results showed that most PYL gene expression levels were up-regulated. Furthermore, with different treatments about 3h, the relative expression of PYL8 was up-regulated and more than 20 times higher than 0h. It indicated that this gene may play an important role in abiotic stress.

Way out there: pathogens, health, and condition of overwintering salmon in the Gulf of Alaska

Salmon are keystone species across the North Pacific, supporting ecosystems, commercial opportunities, and cultural identity. Nevertheless, many wild salmon stocks have experienced significant declines. Salmon restoration efforts focus on fresh and coastal waters, but little is known about the open ocean environment. Here we use high throughput RT-qPCR tools to provide the first report on the health, condition, and infection profile of coho, chum, pink, and sockeye salmon in the Gulf of Alaska during the 2019 winter. We found lower infectious agent number, diversity, and burden compared with coastal British Columbia in all species except coho, which exhibited elevated stock-specific infection profiles. We identified Loma sp. and Ichthyophonus hoferi as key pathogens, suggesting transmission in the open ocean. Reduced prey availability, potentially linked to change in ocean conditions due to an El Niño event, correlated with energetic deficits and immunosuppression in salmon. Immunosuppressed individuals showed higher relative infection burden and higher prevalence of opportunistic pathogens. We highlight the cumulative effects of infection and environmental stressors on overwintering salmon, establishing a baseline to document the impacts of a changing ocean on salmon.

Characterizing methanol metabolism-related promoters for metabolic engineering of Ogataea polymorpha

Promoters play an important role in regulating gene expression, and construction of microbial cell factories requires multiple promoters for balancing the metabolic pathways. However, there are only a limited number of characterized promoters for gene expression in the methylotrophic yeast Ogataea polymorpha, which hampers the extensive harnessing of this important yeast toward a cell factory. Here we characterized the promoters of methanol utilization pathway, precursor supply pathway, and reactive oxygen species (ROS) defense system, by using a green fluorescence protein variant (GFP_UV) as a quantification signal. Finally, the characterized promoters were used for tuning a fatty alcohol biosynthetic pathway in O. polymorpha and realized fatty alcohol production from methanol. This promoter box should be helpful for gene expression and pathway optimization in the methylotrophic yeast O. polymorpha. KEY POINTS : • 22 promoters related to methanol metabolism were characterized in O. polymorpha. • Promoter truncation resulted shorter and compact promoters. • Promoters with various strengths were used for regulating a fatty alcohol biosynthesis from methanol.

Post-translational modifications of proteins associated with yeast peroxisome membrane: An essential mode of regulatory mechanism

Peroxisomes are single membrane‐bound organelles important for the optimum functioning of eukaryotic cells. Seminal discoveries in the field of peroxisomes are made using yeast as a model. Several proteins required for the biogenesis and function of peroxisomes are identified to date. As with proteins involved in other major cellular pathways, peroxisomal proteins are also subjected to regulatory post‐translational modifications. Identification, characterization and mapping of these modifications to specific amino acid residues on proteins are critical toward understanding their functional significance. Several studies have tried to identify post‐translational modifications of peroxisomal proteins and determine their impact on peroxisome structure and function. In this manuscript, we provide an overview of the various post‐translational modifications that govern the peroxisome dynamics in yeast.