A chimeric porcine reproductive and respiratory syndrome virus 1 strain containing synthetic ORF2-6 genes can trigger T follicular helper cell and heterologous neutralizing antibody responses and confer enhanced cross-protection.

The prevalence of porcine reproductive and respiratory syndrome virus 1 (PRRSV1) isolates has continued to increase in Chinese swine herds in recent years. However, no effective control strategy is available for PRRSV1 infection in China. In this study, we generated the first infectious cDNA clone (rHLJB1) of a Chinese PRRSV1 isolate and subsequently used it as a backbone to construct an ORF2-6 chimeric virus (ORF2-6-CON). This virus contained a synthesized consensus sequence of the PRRSV1 ORF2-6 gene encoding all the envelope proteins. The ORF2-6 consensus sequence shared > 90% nucleotide similarity with four representative strains (Amervac, BJEU06-1, HKEU16 and NMEU09-1) of PRRSV1 in China. ORF2-6-CON had replication efficacy similar to that of the backbone rHLJB1 virus in primary alveolar macrophages (PAMs) and exhibited cell tropism in Marc-145 cells. Piglet inoculation and challenge studies indicated that ORF2-6-CON is not pathogenic to piglets and can induce enhanced cross-protection against a heterologous SD1291 isolate. Notably, ORF2-6-CON inoculation induced higher levels of heterologous neutralizing antibodies (nAbs) against SD1291 than rHLJB1 inoculation, which was concurrent with a higher percentage of T follicular helper (Tfh) cells in tracheobronchial lymph nodes (TBLNs), providing the first clue that porcine Tfh cells are correlated with heterologous PRRSV nAb responses. The number of SD1291-strain-specific IFNγ-secreting cells was similar in ORF2-6-CON-inoculated and rHLJB1-inoculated pigs. Overall, our findings support that the Marc-145-adapted ORF2-6-CON can trigger Tfh cell and heterologous nAb responses to confer improved cross-protection and may serve as a candidate strain for the development of a cross-protective PRRSV1 vaccine.

Semirational Design Based on Consensus Sequences to Balance the Enzyme Activity-Stability Trade-Off.

In this study, the phenomenon of the stability-activity trade-off, which is increasingly recognized in enzyme engineering, was explored. Typically, enhanced stability in enzymes correlates with diminished activity. Utilizing Rosa roxburghii copper-zinc superoxide dismutase (RrCuZnSOD) as a model, single-site mutations were introduced based on a semirational design derived from consensus sequences. The initial set of mutants was selected based on activity, followed by combinatorial mutation. This approach yielded two double-site mutants, D25/A115T (18,688 ± 206 U/mg) and A115T/S135P (18,095 ± 1556 U/mg), exhibiting superior enzymatic properties due to additive and synergistic effects. These mutants demonstrated increased half-lives (T1/2) at 80 °C by 1.2- and 1.6-fold, respectively, and their melting temperatures (Tm) rose by 3.4 and 2.5 °C, respectively, without any loss in activity relative to the wild type. Via an integration of structural analysis and molecular dynamics simulations, we elucidated the underlying mechanism facilitating the concurrent enhancement of both thermostability and enzymatic activity.

Extended Cleavage Specificity of two Hematopoietic Serine Proteases from a Ray-Finned Fish, the Spotted Gar (Lepisosteus oculatus).

The extended cleavage specificities of two hematopoietic serine proteases originating from the ray-finned fish, the spotted gar (Lepisosteus oculatus), have been characterized using substrate phage display. The preference for particular amino acids at and surrounding the cleavage site was further validated using a panel of recombinant substrates. For one of the enzymes, the gar granzyme G, a strict preference for the aromatic amino acid Tyr was observed at the cleavable P1 position. Using a set of recombinant substrates showed that the gar granzyme G had a high selectivity for Tyr but a lower activity for cleaving after Phe but not after Trp. Instead, the second enzyme, gar DDN1, showed a high preference for Leu in the P1 position of substrates. This latter enzyme also showed a high preference for Pro in the P2 position and Arg in both P4 and P5 positions. The selectivity for the two Arg residues in positions P4 and P5 suggests a highly specific substrate selectivity of this enzyme. The screening of the gar proteome with the consensus sequences obtained by substrate phage display for these two proteases resulted in a very diverse set of potential targets. Due to this diversity, a clear candidate for a specific immune function of these two enzymes cannot yet be identified. Antisera developed against the recombinant gar enzymes were used to study their tissue distribution. Tissue sections from juvenile fish showed the expression of both proteases in cells in Peyer's patch-like structures in the intestinal region, indicating they may be expressed in T or NK cells. However, due to the lack of antibodies to specific surface markers in the gar, it has not been possible to specify the exact cellular origin. A marked difference in abundance was observed for the two proteases where gar DDN1 was expressed at higher levels than gar granzyme G. However, both appear to be expressed in the same or similar cells, having a lymphocyte-like appearance.

Thermal Stabilization of a Bacterial Zn(II)-Dependent Phospholipase C through Consensus Sequence Design.

Proteins' extraordinary performance in recognition and catalysis has led to their use in a range of applications. However, proteins obtained from natural sources are oftentimes not suitable for direct use in industrial or diagnostic setups. Natural proteins, evolved to optimally perform a task in physiological conditions, usually lack the stability required to be used in harsher conditions. Therefore, the alteration of the stability of proteins is commonly pursued in protein engineering studies. Here, we achieved a substantial thermal stabilization of a bacterial Zn(II)-dependent phospholipase C by consensus sequence design. We retrieved and analyzed sequenced homologues from different sources, selecting a subset of examples for expression and characterization. A non-natural consensus sequence showed the highest stability and activity among those tested. Comparison of the stability parameters of this stabilized mutant and other natural variants bearing similar mutations allows us to pinpoint the sites most likely to be responsible for the enhancement. Point mutations in these sites alter the unfolding process of the consensus sequence. We show that the stabilized version of the protein retains full activity even in harsh oil degumming conditions, making it suitable for industrial applications.

Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design.

Understanding natural protein evolution and designing novel proteins are motivating interest in development of high-throughput methods to explore large sequence spaces. In this work, we demonstrate the application of multisite λ dynamics (MSλD), a rigorous free energy simulation method, and chemical denaturation experiments to quantify evolutionary selection pressure from sequence-stability relationships and to address questions of design. This study examines a mesophilic phylogenetic clade of ribonuclease H (RNase H), furthering its extensive characterization in earlier studies, focusing on E. coli RNase H (ecRNH) and a more stable consensus sequence (AncCcons) differing at 15 positions. The stabilities of 32,768 chimeras between these two sequences were computed using the MSλD framework. The most stable and least stable chimeras were predicted and tested along with several other sequences, revealing a designed chimera with approximately the same stability increase as AncCcons, but requiring only half the mutations. Comparing the computed stabilities with experiment for 12 sequences reveals a Pearson correlation of 0.86 and root mean squared error of 1.18 kcal/mol, an unprecedented level of accuracy well beyond less rigorous computational design methods. We then quantified selection pressure using a simple evolutionary model in which sequences are selected according to the Boltzmann factor of their stability. Selection temperatures from 110 to 168 K are estimated in three ways by comparing experimental and computational results to evolutionary models. These estimates indicate selection pressure is high, which has implications for evolutionary dynamics and for the accuracy required for design, and suggests accurate high-throughput computational methods like MSλD may enable more effective protein design.

High-fidelity (repeat) consensus sequences from short reads using combined read clustering and assembly.

BACKGROUND: Despite the many cheap and fast ways to generate genomic data, good and exact genome assembly is still a problem, with especially the repeats being vastly underrepresented and often misassembled. As short reads in low coverage are already sufficient to represent the repeat landscape of any given genome, many read cluster algorithms were brought forward that provide repeat identification and classification. But how can trustworthy, reliable and representative repeat consensuses be derived from unassembled genomes? RESULTS: Here, we combine methods from repeat identification and genome assembly to derive these robust consensuses. We test several use cases, such as (1) consensus building from clustered short reads of non-model genomes, (2) from genome-wide amplification setups, and (3) specific repeat-centred questions, such as the linked vs. unlinked arrangement of ribosomal genes. In all our use cases, the derived consensuses are robust and representative. To evaluate overall performance, we compare our high-fidelity repeat consensuses to RepeatExplorer2-derived contigs and check, if they represent real transposable elements as found in long reads. Our results demonstrate that it is possible to generate useful, reliable and trustworthy consensuses from short reads by a combination from read cluster and genome assembly methods in an automatable way. CONCLUSION: We anticipate that our workflow opens the way towards more efficient and less manual repeat characterization and annotation, benefitting all genome studies, but especially those of non-model organisms.

POFUT1-mediated O-fucosylation of glycoproteins expressed in the baculovirus Sf9 insect cell expression system.

The baculovirus-insect cell expression system allows addition of O-fucose to EGF-like domains of glycoproteins, following the action of the protein O-fucosyltransferase 1 named POFUT1. In this study, recombinant Spodoptera frugiperda POFUT1 from baculovirus-infected Sf9 cells was compared to recombinant Mus musculus POFUT1 produced by CHO cells. Contrary to recombinant murine POFUT1 carrying two hybrid and/or complex type N-glycans, Spodoptera frugiperda POFUT1 exhibited paucimannose N-glycans, at least on its highly evolutionary conserved across Metazoa NRT site. The abilities of both recombinant enzymes to add in vitro O -fucose to EGF-like domains of three different recombinant mammalian glycoproteins were then explored. In vitro POFUT1-mediated O-fucosylation experiments, followed by click chemistry and blot analyses, showed that Spodoptera frugiperda POFUT1 was able to add O-fucose to mouse NOTCH1 EGF-like 26 and WIF1 EGF-like 3 domains, similarly to the murine counterpart. As proved by mass spectrometry, full-length human WNT Inhibitor Factor 1 expressed by Sf9 cells was also modified with O-fucose. However, Spodoptera frugiperda POFUT1 was unable to modify the single EGF-like domain of mouse PAMR1 with O-fucose, contrary to murine POFUT1. Absence of orthologous proteins such as PAMR1 in insects may explain the enzyme's difficulty in adding O-fucose to a domain that it never encounters naturally.

Brain-wide correspondence of neuronal epigenomics and distant projections.

Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.

FOXP3 recognizes microsatellites and bridges DNA through multimerization.

FOXP3 is a transcription factor that is essential for the development of regulatory T cells, a branch of T cells that suppress excessive inflammation and autoimmunity1-5. However, the molecular mechanisms of FOXP3 remain unclear. Here we here show that FOXP3 uses the forkhead domain-a DNA-binding domain that is commonly thought to function as a monomer or dimer-to form a higher-order multimer after binding to TnG repeat microsatellites. The cryo-electron microscopy structure of FOXP3 in a complex with T3G repeats reveals a ladder-like architecture, whereby two double-stranded DNA molecules form the two 'side rails' bridged by five pairs of FOXP3 molecules, with each pair forming a 'rung'. Each FOXP3 subunit occupies TGTTTGT within the repeats in a manner that is indistinguishable from that of FOXP3 bound to the forkhead consensus motif (TGTTTAC). Mutations in the intra-rung interface impair TnG repeat recognition, DNA bridging and the cellular functions of FOXP3, all without affecting binding to the forkhead consensus motif. FOXP3 can tolerate variable inter-rung spacings, explaining its broad specificity for TnG-repeat-like sequences in vivo and in vitro. Both FOXP3 orthologues and paralogues show similar TnG repeat recognition and DNA bridging. These findings therefore reveal a mode of DNA recognition that involves transcription factor homomultimerization and DNA bridging, and further implicates microsatellites in transcriptional regulation and diseases.

Unveiling metabolic pathways involved in the extreme desiccation tolerance of an Atacama cyanobacterium.

Gloeocapsopsis dulcis strain AAB1 is an extremely xerotolerant cyanobacterium isolated from the Atacama Desert (i.e., the driest and oldest desert on Earth) that holds astrobiological significance due to its ability to biosynthesize compatible solutes at ultra-low water activities. We sequenced and assembled the G. dulcis genome de novo using a combination of long- and short-read sequencing, which resulted in high-quality consensus sequences of the chromosome and two plasmids. We leveraged the G. dulcis genome to generate a genome-scale metabolic model (iGd895) to simulate growth in silico. iGd895 represents, to our knowledge, the first genome-scale metabolic reconstruction developed for an extremely xerotolerant cyanobacterium. The model's predictive capability was assessed by comparing the in silico growth rate with in vitro growth rates of G. dulcis, in addition to the synthesis of trehalose. iGd895 allowed us to explore simulations of key metabolic processes such as essential pathways for water-stress tolerance, and significant alterations to reaction flux distribution and metabolic network reorganization resulting from water limitation. Our study provides insights into the potential metabolic strategies employed by G. dulcis, emphasizing the crucial roles of compatible solutes, metabolic water, energy conservation, and the precise regulation of reaction rates in their adaptation to water stress.

Enhancement of Neutralization Responses through Sequential Immunization of Stable Env Trimers Based on Consensus Sequences from Select Time Points by Mimicking Natural Infection.

HIV-1 vaccines have been challenging to develop, partly due to the high level of genetic variation in its genome. Thus, a vaccine that can induce cross-reactive neutralization activities will be needed. Studies on the co-evolution of antibodies and viruses indicate that mimicking the natural infection is likely to induce broadly neutralizing antibodies (bnAbs). We generated the consensus Env sequence for each time point in subject CH505, who developed broad neutralization activities, and selected five critical time points before broad neutralization was detected. These consensus sequences were designed to express stable Env trimers. Priming with the transmitted/founder Env timer and sequential boosting with these consensus Env trimers from different time points induced broader and more potent neutralizing activities than the BG505 Env trimer in guinea pigs. Analysis of the neutralization profiles showed that sequential immunization of Env trimers favored nAbs with gp120/gp41 interface specificity while the BG505 Env trimer favored nAbs with V2 specificity. The unique features such as consensus sequences, stable Env trimers and the sequential immunization to mimic natural infection likely has allowed the induction of improved neutralization responses.

Towards in silico CLIP-seq: predicting protein-RNA interaction via sequence-to-signal learning.

We present RBPNet, a novel deep learning method, which predicts CLIP-seq crosslink count distribution from RNA sequence at single-nucleotide resolution. By training on up to a million regions, RBPNet achieves high generalization on eCLIP, iCLIP and miCLIP assays, outperforming state-of-the-art classifiers. RBPNet performs bias correction by modeling the raw signal as a mixture of the protein-specific and background signal. Through model interrogation via Integrated Gradients, RBPNet identifies predictive sub-sequences that correspond to known and novel binding motifs and enables variant-impact scoring via in silico mutagenesis. Together, RBPNet improves imputation of protein-RNA interactions, as well as mechanistic interpretation of predictions.

General features of transmembrane beta barrels from a large database.

Large datasets contribute new insights to subjects formerly investigated by exemplars. We used coevolution data to create a large, high-quality database of transmembrane ß-barrels (TMBB). By applying simple feature detection on generated evolutionary contact maps, our method (IsItABarrel) achieves 95.88% balanced accuracy when discriminating among protein classes. Moreover, comparison with IsItABarrel revealed a high rate of false positives in previous TMBB algorithms. In addition to being more accurate than previous datasets, our database (available online) contains 1,938,936 bacterial TMBB proteins from 38 phyla, respectively, 17 and 2.2 times larger than the previous sets TMBB-DB and OMPdb. We anticipate that due to its quality and size, the database will serve as a useful resource where high-quality TMBB sequence data are required. We found that TMBBs can be divided into 11 types, three of which have not been previously reported. We find tremendous variance in proteome percentage among TMBB-containing organisms with some using 6.79% of their proteome for TMBBs and others using as little as 0.27% of their proteome. The distribution of the lengths of the TMBBs is suggestive of previously hypothesized duplication events. In addition, we find that the C-terminal ß-signal varies among different classes of bacteria though its consensus sequence is LGLGYRF. However, this ß-signal is only characteristic of prototypical TMBBs. The ten non-prototypical barrel types have other C-terminal motifs, and it remains to be determined if these alternative motifs facilitate TMBB insertion or perform any other signaling function.

Computational Evaluation of Peroxisomal Targeting Signals in Metazoa.

Most soluble proteins enclosed in peroxisomes encode either type-1 or type-2 peroxisomal targeting signals (PTS1 or PTS2), which act as postal codes and define the proteins' intracellular destination. Thus, various computational programs have been developed to evaluate the probability of specific peptide sequences for being a functional PTS or to scan the primary sequence of proteins for such signals. Among these prediction algorithms the PTS1-predictor ( https://mendel.imp.ac.at/pts1/ ) has been amply used, but the research logic of this and other PTS1 prediction tools is occasionally misjudged giving rise to characteristic pitfalls. Here, a proper utilization of the PTS1-predictor is introduced together with a framework of additional tests to increase the validity of the interpretation of results. Moreover, a list of possible causes for a mismatch between results of such predictions and experimental outcomes is provided. However, the foundational arguments apply to other prediction tools for PTS1 motifs as well.

PURC Provides Improved Sequence Inference for Polyploid Phylogenetics and Other Manifestations of the Multiple-Copy Problem.

Inferring the true biological sequences from amplicon mixtures remains a difficult bioinformatics problem. The traditional approach is to cluster sequencing reads by similarity thresholds and treat the consensus sequence of each cluster as an "operational taxonomic unit" (OTU). Recently, this approach has been improved by model-based methods that correct PCR and sequencing errors in order to infer "amplicon sequence variants" (ASVs). To date, ASV approaches have been used primarily in metagenomics, but they are also useful for determining homeologs in polyploid organisms. To facilitate the usage of ASV methods among polyploidy researchers, we incorporated ASV inference alongside OTU clustering in PURC v2.0, a major update to PURC (Pipeline for Untangling Reticulate Complexes). In addition, PURC v2.0 features faster demultiplexing than the original version and has been updated to be compatible with Python 3. In this chapter we present results indicating that using the ASV approach is more likely to infer the correct biological sequences in comparison to the earlier OTU-based PURC and describe how to prepare sequencing data, run PURC v2.0 under several different modes, and interpret the output.

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

INTRODUCTION: Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown. MATERIAL AND METHODS: We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina. RESULTS: We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination. DISCUSSION: Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

Combined proteomic and biochemical analyses redefine the consensus sequence requirement for epidermal growth factor-like domain hydroxylation.

Epidermal growth factor-like domains (EGFDs) have important functions in cell-cell signaling. Both secreted and cell surface human EGFDs are subject to extensive modifications, including aspartate and asparagine residue C3-hydroxylations catalyzed by the 2-oxoglutarate oxygenase aspartate/asparagine-ß-hydroxylase (AspH). Although genetic studies show AspH is important in human biology, studies on its physiological roles have been limited by incomplete knowledge of its substrates. Here, we redefine the consensus sequence requirements for AspH-catalyzed EGFD hydroxylation based on combined analysis of proteomic mass spectrometric data and mass spectrometry-based assays with isolated AspH and peptide substrates. We provide cellular and biochemical evidence that the preferred site of EGFD hydroxylation is embedded within a disulfide-bridged macrocycle formed of 10 amino acid residues. This definition enabled the identification of previously unassigned hydroxylation sites in three EGFDs of human fibulins as AspH substrates. A non-EGFD containing protein, lymphocyte antigen-6/plasminogen activator urokinase receptor domain containing protein 6B (LYPD6B) was shown to be a substrate for isolated AspH, but we did not observe evidence for LYPD6B hydroxylation in cells. AspH-catalyzed hydroxylation of fibulins is of particular interest given their important roles in extracellular matrix dynamics. In conclusion, these results lead to a revision of the consensus substrate requirements for AspH and expand the range of observed and potential AspH-catalyzed hydroxylation in cells, which will enable future study of the biological roles of AspH.

MAECI: A pipeline for generating consensus sequence with nanopore sequencing long-read assembly and error correction.

Nanopore sequencing produces long reads and offers unique advantages over next-generation sequencing, especially for the assembly of draft bacterial genomes with improved completeness. However, assembly errors can occur due to data characteristics and assembly algorithms. To address these issues, we developed MAECI, a pipeline for generating consensus sequences from multiple assemblies of the same nanopore sequencing data and error correction. Systematic evaluation showed that MAECI is an efficient and effective pipeline to improve the accuracy and completeness of bacterial genome assemblies. The available codes and implementation are at https://github.com/langjidong/MAECI.

Uncovering the mesendoderm gene regulatory network through multi-omic data integration.

Mesendodermal specification is one of the earliest events in embryogenesis, where cells first acquire distinct identities. Cell differentiation is a highly regulated process that involves the function of numerous transcription factors (TFs) and signaling molecules, which can be described with gene regulatory networks (GRNs). Cell differentiation GRNs are difficult to build because existing mechanistic methods are low throughput, and high-throughput methods tend to be non-mechanistic. Additionally, integrating highly dimensional data composed of more than two data types is challenging. Here, we use linked self-organizing maps to combine chromatin immunoprecipitation sequencing (ChIP-seq)/ATAC-seq with temporal, spatial, and perturbation RNA sequencing (RNA-seq) data from Xenopus tropicalis mesendoderm development to build a high-resolution genome scale mechanistic GRN. We recover both known and previously unsuspected TF-DNA/TF-TF interactions validated through reporter assays. Our analysis provides insights into transcriptional regulation of early cell fate decisions and provides a general approach to building GRNs using highly dimensional multi-omic datasets.

Conserved Motifs and Domains in Members of Pospiviroidae.

In 1985, Keese and Symons proposed a hypothesis on the sequence and secondary structure of viroids from the family Pospiviroidae: their secondary structure can be subdivided into five structural and functional domains and "viroids have evolved by rearrangement of domains between different viroids infecting the same cell and subsequent mutations within each domain"; this article is one of the most cited in the field of viroids. Employing the pairwise alignment method used by Keese and Symons and in addition to more recent methods, we tried to reproduce the original results and extent them to further members of Pospiviroidae which were unknown in 1985. Indeed, individual members of Pospiviroidae consist of a patchwork of sequence fragments from the family but the lengths of fragments do not point to consistent points of rearrangement, which is in conflict with the original hypothesis of fixed domain borders.