MetaLogo: a heterogeneity-aware sequence logo generator and aligner

Lead Informed Artificial Intelligence Mining of Antitubercular Host Defense Peptides

Identifying host defense peptides (HDPs) that are effective against drug-resistant infections is challenging due to their vast sequence space. Artificial intelligence (AI)-guided design can accelerate HDP discovery, but it traditionally requires large data sets to operationalize. We report an AI workflow that utilizes limited data sets (∼100 peptides) to uncover potent, selective, and safe HDPs by informing selection through lead candidate mutational scanning. This approach, referred to as Lead Informed Machine Interrogation of Therapeutic Sequences (LIMITS), is applied against the exemplary pathogen Mycobacterium tuberculosis. Experimental validation of predicted sequences shows nearly an order of magnitude improvement in potency, selectivity, and safety, relative to the initial template. Post hoc analysis suggests sequence length may be a unique and underappreciated driver of antitubercular HDP activity. These results demonstrate that, with continued development, the LIMITS approach can identify selective HDPs under data-limited conditions and elucidate structure-function-performance relationships previously hidden in biologic complexity.

Putative MutS2 Homologs in Algae: More Goods in Shopping Bag?

MutS2 proteins are presumably involved in either control of recombination or translation quality control in bacteria. MutS2 homologs have been found in plants and some algae; however, their actual diversity in eukaryotes remains unknown. We found putative MutS2 homologs in various species of photosynthetic eukaryotes and performed a detailed analysis of the revealed amino acid sequences. Three groups of homologs were distinguished depending on their domain composition: MutS2 homologs with full set of specific domains, MutS2-like sequences without endonuclease Smr domain, and MutS2-like homologs lacking Smr and clamp in domain IV, the extreme form of which are proteins with only a complete ATPase domain. We clarified the information about amino acid composition and set of specific motifs in the conserved domains in MutS2 and MutS2-like sequences. The models of the predicted tertiary structure were obtained for each group of homologs. The phylogenetic analysis demonstrated that all eukaryotic sequences split into two large groups. The first group included homologs belonging to species of Archaeplastida and a subset of haptophyte homologs, while the second-sequences of organisms from CASH groups (cryptophytes, alveolates, stramenopiles, haptophytes) and chlorarachniophytes. The cyanobacterial MutS2 clustered together with the first group, and proteins belonging to Deltaproteobacteria (orders Myxococcales and Bradymonadales) showed phylogenetic affinity to the CASH-including group with strong support. The observed tree pattern did not support a clear differentiation of eukaryotes into lineages with red and green algae-derived plastids. The results are discussed in the context of current conceptions of serial endosymbioses and genetic mosaicism in algae with complex plastids.

Evolutionary origins and innovations sculpting the mammalian PRPS enzyme complex

The phosphoribosyl pyrophosphate synthetase (PRPS) enzyme conducts a chokepoint reaction connecting central carbon metabolism and nucleotide production pathways, making it essential for life1,2. Here, we show that the presence of multiple PRPS-encoding genes is a hallmark trait of eukaryotes, and we trace the evolutionary origins and define the individual functions of each of the five mammalian PRPS homologs - three isozymes (one testis-restricted)3,4 and two non-enzymatic associated proteins (APs)5,6 - which we demonstrate operate together as a large molecular weight complex capable of attaining a heterogeneous array of functional multimeric configurations. Employing a repertoire of isogenic fibroblast clones in all viable individual or combinatorial assembly states, we define preferential interactions between subunits, and we show that cells lacking PRPS2, PRPSAP1, and PRPSAP2 render PRPS1 into aberrant homo-oligomeric assemblies with diminished metabolic flux and impaired proliferative capacity. We demonstrate how numerous evolutionary innovations in the duplicated genes have created specialized roles for individual complex members and identify translational control mechanisms that enable fine-tuned regulation of PRPS assembly and activity, which provide clues into the positive and negative selective pressures that facilitate metabolic flexibility and tissue specialization in advanced lifeforms. Collectively, our study demonstrates how evolution has transformed a single PRPS gene into a multimeric complex endowed with functional and regulatory features that govern cellular biochemistry.

DeepCBA: A deep learning framework for gene expression prediction in maize based on DNA sequences and chromatin interactions

Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome, which has an important impact on gene expression, transcriptional regulation, and phenotypic traits. To date, several methods have been developed for predicting gene expression. However, existing methods do not take into consideration the effect of chromatin interactions on target gene expression, thus potentially reducing the accuracy of gene expression prediction and mining of important regulatory elements. In this study, we developed a highly accurate deep learning-based gene expression prediction model (DeepCBA) based on maize chromatin interaction data. Compared with existing models, DeepCBA exhibits higher accuracy in expression classification and expression value prediction. The average Pearson correlation coefficients (PCCs) for predicting gene expression using gene promoter proximal interactions, proximal-distal interactions, and both proximal and distal interactions were 0.818, 0.625, and 0.929, respectively, representing an increase of 0.357, 0.16, and 0.469 over the PCCs obtained with traditional methods that use only gene proximal sequences. Some important motifs were identified through DeepCBA; they were enriched in open chromatin regions and expression quantitative trait loci and showed clear tissue specificity. Importantly, experimental results for the maize flowering-related gene ZmRap2.7 and the tillering-related gene ZmTb1 demonstrated the feasibility of DeepCBA for exploration of regulatory elements that affect gene expression. Moreover, promoter editing and verification of two reported genes (ZmCLE7 and ZmVTE4) demonstrated the utility of DeepCBA for the precise design of gene expression and even for future intelligent breeding. DeepCBA is available at http://www.deepcba.com/ or http://124.220.197.196/.

Identification of a highly efficient chloroplast-targeting peptide for plastid engineering

Plastids are pivotal target organelles for comprehensively enhancing photosynthetic and metabolic traits in plants via plastid engineering. Plastidial proteins predominantly originate in the nucleus and must traverse membrane-bound multiprotein translocons to access these organelles. This import process is meticulously regulated by chloroplast-targeting peptides (cTPs). Whereas many cTPs have been employed to guide recombinantly expressed functional proteins to chloroplasts, there is a critical need for more efficient cTPs. Here, we performed a comprehensive exploration and comparative assessment of an advanced suite of cTPs exhibiting superior targeting capabilities. We employed a multifaceted approach encompassing computational prediction, in planta expression, fluorescence tracking, and in vitro chloroplast import studies to identify and analyze 88 cTPs associated with Arabidopsis thaliana mutants with phenotypes linked to chloroplast function. These polypeptides exhibited distinct abilities to transport green fluorescent protein (GFP) to various compartments within leaf cells, particularly chloroplasts. A highly efficient cTP derived from Arabidopsis plastid ribosomal protein L35 (At2g24090) displayed remarkable effectiveness in chloroplast localization. This cTP facilitated the activities of chloroplast-targeted RNA-processing proteins and metabolic enzymes within plastids. This cTP could serve as an ideal transit peptide for precisely targeting biomolecules to plastids, leading to advancements in plastid engineering.

Combined effect of SAR-endolysin LysKpV475 with polymyxin B and Salmonella bacteriophage phSE-5

Endolysins are bacteriophage (or phage)-encoded enzymes that catalyse the peptidoglycan breakdown in the bacterial cell wall. The exogenous action of recombinant phage endolysins against Gram-positive organisms has been extensively studied. However, the outer membrane acts as a physical barrier when considering the use of recombinant endolysins to combat Gram-negative bacteria. This study aimed to evaluate the antimicrobial activity of the SAR-endolysin LysKpV475 against Gram-negative bacteria as single or combined therapies, using an outer membrane permeabilizer (polymyxin B) and a phage, free or immobilized in a pullulan matrix. In the first step, the endolysin LysKpV475 in solution, alone and combined with polymyxin B, was tested in vitro and in vivo against ten Gram-negative bacteria, including highly virulent strains and multidrug-resistant isolates. In the second step, the lyophilized LysKpV475 endolysin was combined with the phage phSE-5 and investigated, free or immobilized in a pullulan matrix, against Salmonella enterica subsp. enterica serovar Typhimurium ATCC 13311. The bacteriostatic action of purified LysKpV475 varied between 8.125 μg ml-1 against Pseudomonas aeruginosa ATCC 27853, 16.25 μg ml-1 against S. enterica Typhimurium ATCC 13311, and 32.50 μg ml-1 against Klebsiella pneumoniae ATCC BAA-2146 and Enterobacter cloacae P2224. LysKpV475 showed bactericidal activity only for P. aeruginosa ATCC 27853 (32.50 μg ml-1) and P. aeruginosa P2307 (65.00 μg ml-1) at the tested concentrations. The effect of the LysKpV475 combined with polymyxin B increased against K. pneumoniae ATCC BAA-2146 [fractional inhibitory concentration index (FICI) 0.34; a value lower than 1.0 indicates an additive/combined effect] and S. enterica Typhimurium ATCC 13311 (FICI 0.93). A synergistic effect against S. enterica Typhimurium was also observed when the lyophilized LysKpV475 at ⅔ MIC was combined with the phage phSE-5 (m.o.i. of 100). The lyophilized LysKpV475 immobilized in a pullulan matrix maintained a significant Salmonella reduction of 2 logs after 6 h of treatment. These results demonstrate the potential of SAR-endolysins, alone or in combination with other treatments, in the free form or immobilized in solid matrices, which paves the way for their application in different areas, such as in biocontrol at the food processing stage, biosanitation of food contact surfaces and biopreservation of processed food in active food packing.

Monkeypox virus genomic accordion strategies

The 2023 monkeypox (mpox) epidemic was caused by a subclade IIb descendant of a monkeypox virus (MPXV) lineage traced back to Nigeria in 1971. Person-to-person transmission appears higher than for clade I or subclade IIa MPXV, possibly caused by genomic changes in subclade IIb MPXV. Key genomic changes could occur in the genome's low-complexity regions (LCRs), which are challenging to sequence and are often dismissed as uninformative. Here, using a combination of highly sensitive techniques, we determine a high-quality MPXV genome sequence of a representative of the current epidemic with LCRs resolved at unprecedented accuracy. This reveals significant variation in short tandem repeats within LCRs. We demonstrate that LCR entropy in the MPXV genome is significantly higher than that of single-nucleotide polymorphisms (SNPs) and that LCRs are not randomly distributed. In silico analyses indicate that expression, translation, stability, or function of MPXV orthologous poxvirus genes (OPGs), including OPG153, OPG204, and OPG208, could be affected in a manner consistent with the established "genomic accordion" evolutionary strategies of orthopoxviruses. We posit that genomic studies focusing on phenotypic MPXV differences should consider LCR variability.

AI and Knowledge-Based Method for Rational Design of Escherichia coli Sigma70 Promoters

Expanding sigma70 promoter libraries can support the engineering of metabolic pathways and enhance recombinant protein expression. Herein, we developed an artificial intelligence (AI) and knowledge-based method for the rational design of sigma70 promoters. Strong sigma70 promoters were identified by using high-throughput screening (HTS) with enhanced green fluorescent protein (eGFP) as a reporter gene. The features of these strong promoters were adopted to guide promoter design based on our previous reported deep learning model. In the following case study, the obtained strong promoters were used to express collagen and microbial transglutaminase (mTG), resulting in increased expression levels by 81.4% and 33.4%, respectively. Moreover, these constitutive promoters achieved soluble expression of mTG-activating protease and contributed to active mTG expression in Escherichia coli. The results suggested that the combined method may be effective for promoter engineering.

Parallel evolution of picobirnaviruses from distinct ancestral origins

IMPORTANCE

Picobirnaviruses (PBVs) are highly heterogeneous viruses encoding a capsid and RdRp. Detected in a wide variety of animals with and without disease, their association with gastrointestinal and respiratory infections, and consequently their public health importance, has rightly been questioned. Determining the "true" host of Picobirnavirus lies at the center of this debate, as evidence exists for them having both vertebrate and prokaryotic origins. Using integrated and time-stamped phylogenetic approaches, we show they are contemporaneous viruses descending from two different ancestors: avian Reovirus and fungal Partitivirus. The fungal PBV-R2 species emerged with a single segment (RdRp) until it acquired a capsid from vertebrate PBV-R1 and PBV-R3 species. Protein and RNA folding analyses revealed how the former came to resemble the latter over time. Thus, parallel evolution from disparate hosts has driven the adaptation and genetic diversification of the Picobirnaviridae family.

Deep Learning-Assisted Design of Novel Promoters in Escherichia coli

Deep learning (DL) approaches have the ability to accurately recognize promoter regions and predict their strength. Here, the potential for controllably designing active Escherichia coli promoter is explored by combining multiple deep learning models. First, "DRSAdesign," which relies on a diffusion model to generate different types of novel promoters is created, followed by predicting whether they are real or fake and strength. Experimental validation showed that 45 out of 50 generated promoters are active with high diversity, but most promoters have relatively low activity. Next, "Ndesign," which relies on generating random sequences carrying functional -35 and -10 motifs of the sigma70 promoter is introduced, and their strength is predicted using the designed DL model. The DL model is trained and validated using 200 and 50 generated promoters, and displays Pearson correlation coefficients of 0.49 and 0.43, respectively. Taking advantage of the DL models developed in this work, possible 6-mers are predicted as key functional motifs of the sigma70 promoter, suggesting that promoter recognition and strength prediction mainly rely on the accommodation of functional motifs. This work provides DL tools to design promoters and assess their functions, paving the way for DL-assisted metabolic engineering.

From single- to multi-omics: future research trends in medicinal plants

Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomics, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.

EbfC/YbaB: A Widely Distributed Nucleoid-Associated Protein in Prokaryotes

Genomic compaction is an essential characteristic of living organisms. Nucleoid-associated proteins (NAPs) are a group of small proteins that play crucial roles in chromosome architecture and affect DNA replication, transcription, and recombination by imposing topological alterations in genomic DNA, thereby modulating global gene expression. EbfC/YbaB was first described as a DNA-binding protein of Borrelia burgdorferi that regulates the expression of surface lipoproteins with roles in virulence. Further studies indicated that this protein binds specifically and non-specifically to DNA and colocalises with nucleoids in this bacterium. The data showed that this protein binds to DNA as a homodimer, although it can form other organised structures. Crystallography analysis indicated that the protein possesses domains responsible for protein–protein interactions and forms a “tweezer” structure probably involved in DNA binding. Moreover, sequence analysis revealed conserved motifs that may be associated with dimerisation. Structural analysis also showed that the tridimensional structure of EbfC/YbaB is highly conserved within the bacterial domain. The DNA-binding activity was observed in different bacterial species, suggesting that this protein can protect DNA during stress conditions. These findings indicate that EbfC/YbaB is a broadly distributed NAP. Here, we present a review of the existing data on this NAP.