Diverse crystalline protein scaffolds through metal-dependent polymorphism.

As protein crystals are increasingly finding diverse applications as scaffolds, controlled crystal polymorphism presents a facile strategy to form crystalline assemblies with controllable porosity with minimal to no protein engineering. Polymorphs of consensus tetratricopeptide repeat proteins with varying porosity were obtained through co-crystallization with metal salts, exploiting the innate metal ion geometric requirements. A single structurally exposed negative amino acid cluster was responsible for metal coordination, despite the abundance of negatively charged residues. Density functional theory calculations showed that while most of the crystals were the most thermodynamically stable assemblies, some were kinetically trapped states. Thus, crystalline porosity diversity is achieved and controlled with metal coordination, opening a new scope in the application of proteins as biocompatible protein-metal-organic frameworks (POFs). In addition, metal-dependent polymorphic crystals allow direct comparison of metal coordination preferences.

Enhancing missense variant pathogenicity prediction with protein language models using VariPred.

Computational approaches for predicting the pathogenicity of genetic variants have advanced in recent years. These methods enable researchers to determine the possible clinical impact of rare and novel variants. Historically these prediction methods used hand-crafted features based on structural, evolutionary, or physiochemical properties of the variant. In this study we propose a novel framework that leverages the power of pre-trained protein language models to predict variant pathogenicity. We show that our approach VariPred (Variant impact Predictor) outperforms current state-of-the-art methods by using an end-to-end model that only requires the protein sequence as input. Using one of the best-performing protein language models (ESM-1b), we establish a robust classifier that requires no calculation of structural features or multiple sequence alignments. We compare the performance of VariPred with other representative models including 3Cnet, Polyphen-2, REVEL, MetaLR, FATHMM and ESM variant. VariPred performs as well as, or in most cases better than these other predictors using six variant impact prediction benchmarks despite requiring only sequence data and no pre-processing of the data.

Single-cell and spatial RNA sequencing reveal the spatiotemporal trajectories of fruit senescence.

The senescence of fruit is a complex physiological process, with various cell types within the pericarp, making it highly challenging to elucidate their individual roles in fruit senescence. In this study, a single-cell expression atlas of the pericarp of pitaya (Hylocereus undatus) is constructed, revealing exocarp and mesocarp cells undergoing the most significant changes during the fruit senescence process. Pseudotime analysis establishes cellular differentiation and gene expression trajectories during senescence. Early-stage oxidative stress imbalance is followed by the activation of resistance in exocarp cells, subsequently senescence-associated proteins accumulate in the mesocarp cells at late-stage senescence. The central role of the early response factor HuCMB1 is unveiled in the senescence regulatory network. This study provides a spatiotemporal perspective for a deeper understanding of the dynamic senescence process in plants.

sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome.

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

High-throughput Selection of Human de novo-emerged sORFs with High Folding Potential.

De novo genes emerge from previously noncoding stretches of the genome. Their encoded de novo proteins are generally expected to be similar to random sequences and, accordingly, with no stable tertiary fold and high predicted disorder. However, structural properties of de novo proteins and whether they differ during the stages of emergence and fixation have not been studied in depth and rely heavily on predictions. Here we generated a library of short human putative de novo proteins of varying lengths and ages and sorted the candidates according to their structural compactness and disorder propensity. Using Förster resonance energy transfer combined with Fluorescence-activated cell sorting, we were able to screen the library for most compact protein structures, as well as most elongated and flexible structures. We find that compact de novo proteins are on average slightly shorter and contain lower predicted disorder than less compact ones. The predicted structures for most and least compact de novo proteins correspond to expectations in that they contain more secondary structure content or higher disorder content, respectively. Our experiments indicate that older de novo proteins have higher compactness and structural propensity compared with young ones. We discuss possible evolutionary scenarios and their implications underlying the age-dependencies of compactness and structural content of putative de novo proteins.

Novel genetic variant in hereditary spastic paraparesis.

A man in his 30s was referred to neurology with right-sided paraesthesia, tremors, chest pain and lower urinary tract and erectile dysfunction. He had a medical history of left acetabular dysplasia, and subjective memory impairment, the latter being in the context of depression and chronic pain with opioid use. There was no notable family history. On examination, he had a spastic paraparesis. Imaging revealed atrophy of the thoracic spine. Lumbar puncture demonstrated a raised protein but other constituents were normal, including no presence of oligoclonal bands. Genetic testing revealed a novel heterozygous likely pathogenic SPAST variant c. 1643A>T p.(Asp548Val), confirming the diagnosis of hereditary spastic paraparesis. Symptomatic treatment with physiotherapy and antispasmodic therapy was initiated. This is the first study reporting a patient with this SPAST variant. Ensembl variant effect predictor was used, with the application of computational variant prediction tools providing support that the variant we have identified is likely deleterious and damaging. Our variant CADD score was high, indicating that our identified variant was a highly deleterious substitution.

A fast comparative genome browser for diverse bacteria and archaea.

Genome sequencing has revealed an incredible diversity of bacteria and archaea, but there are no fast and convenient tools for browsing across these genomes. It is cumbersome to view the prevalence of homologs for a protein of interest, or the gene neighborhoods of those homologs, across the diversity of the prokaryotes. We developed a web-based tool, fast.genomics, that uses two strategies to support fast browsing across the diversity of prokaryotes. First, the database of genomes is split up. The main database contains one representative from each of the 6,377 genera that have a high-quality genome, and additional databases for each taxonomic order contain up to 10 representatives of each species. Second, homologs of proteins of interest are identified quickly by using accelerated searches, usually in a few seconds. Once homologs are identified, fast.genomics can quickly show their prevalence across taxa, view their neighboring genes, or compare the prevalence of two different proteins. Fast.genomics is available at https://fast.genomics.lbl.gov.

The Association between Histidine-Rich Glycoprotein rs10770 Genotype and Recurrent Miscarriage in Iranian Women.

Purpose: Recurrent miscarriage (RM) is a significant reproductive concern affecting numerous women globally. Genetic factors are believed to play a crucial role in RM, making the histidine-rich glycoprotein (HRG) gene, a topic of interest due to its potential involvement in angiogenesis. This study is aimed at investigating the association between the HRG rs10770 genotype and RM. Method: Blood samples were collected from a total of 200 women at the beginning of the study. Subsequently, a comparative analysis was conducted between the blood samples of 100 women with a history of RM (case group) and the blood samples of another 100 healthy women (control group). HRG rs10770 genotyping was performed through polymerase chain reaction restriction-fragment length polymorphism (PCR-RFLP), followed by statistical analysis to evaluate the relationship between HRG rs10770 genotype and RM. Results: The results indicated a significant statistical difference between the C/C genotype (OR = 3.32, CI: 1.22-9.04, p = 0.01) and the C/T genotype (OR = 1.24, CI: 0.67-2.30, p = 0.47) in both the case and control groups. Additionally, a significant correlation was observed in the C allelic frequency among RM participants compared to the control group (OR = 1.65, CI: 1.06-2.58, p = 0.02). Conclusion: The study highlights the importance of HRG rs10770 in understanding RM, shedding light on its implications for reproductive health. Furthermore, it became evident that women carrying the homozygous C/C genotype exhibited increased susceptibility to the risk of RM.

Combining Rosetta Sequence Design with Protein Language Model Predictions Using Evolutionary Scale Modeling (ESM) as Restraint.

Computational protein sequence design has the ambitious goal of modifying existing or creating new proteins; however, designing stable and functional proteins is challenging without predictability of protein dynamics and allostery. Informing protein design methods with evolutionary information limits the mutational space to more native-like sequences and results in increased stability while maintaining functions. Recently, language models, trained on millions of protein sequences, have shown impressive performance in predicting the effects of mutations. Assessing Rosetta-designed sequences with a language model showed scores that were worse than those of their original sequence. To inform Rosetta design protocols with language model predictions, we added a new metric to restrain the energy function during design using the Evolutionary Scale Modeling (ESM) model. The resulting sequences have better language model scores and similar sequence recovery, with only a minor decrease in the fitness as assessed by Rosetta energy. In conclusion, our work combines the strength of recent machine learning approaches with the Rosetta protein design toolbox.

Enhancing coevolutionary signals in protein-protein interaction prediction through clade-wise alignment integration.

Protein-protein interactions (PPIs) play essential roles in most biological processes. The binding interfaces between interacting proteins impose evolutionary constraints that have successfully been employed to predict PPIs from multiple sequence alignments (MSAs). To construct MSAs, critical choices have to be made: how to ensure the reliable identification of orthologs, and how to optimally balance the need for large alignments versus sufficient alignment quality. Here, we propose a divide-and-conquer strategy for MSA generation: instead of building a single, large alignment for each protein, multiple distinct alignments are constructed under distinct clades in the tree of life. Coevolutionary signals are searched separately within these clades, and are only subsequently integrated using machine learning techniques. We find that this strategy markedly improves overall prediction performance, concomitant with better alignment quality. Using the popular DCA algorithm to systematically search pairs of such alignments, a genome-wide all-against-all interaction scan in a bacterial genome is demonstrated. Given the recent successes of AlphaFold in predicting direct PPIs at atomic detail, a discover-and-refine approach is proposed: our method could provide a fast and accurate strategy for pre-screening the entire genome, submitting to AlphaFold only promising interaction candidates-thus reducing false positives as well as computation time.

The impact of genetically controlled splicing on exon inclusion and protein structure.

Common variants affecting mRNA splicing are typically identified though splicing quantitative trait locus (sQTL) mapping and have been shown to be enriched for GWAS signals by a similar degree to eQTLs. However, the specific splicing changes induced by these variants have been difficult to characterize, making it more complicated to analyze the effect size and direction of sQTLs, and to determine downstream splicing effects on protein structure. In this study, we catalogue sQTLs using exon percent spliced in (PSI) scores as a quantitative phenotype. PSI is an interpretable metric for identifying exon skipping events and has some advantages over other methods for quantifying splicing from short read RNA sequencing. In our set of sQTL variants, we find evidence of selective effects based on splicing effect size and effect direction, as well as exon symmetry. Additionally, we utilize AlphaFold2 to predict changes in protein structure associated with sQTLs overlapping GWAS traits, highlighting a potential new use-case for this technology for interpreting genetic effects on traits and disorders.

A Single-Cell Transcriptome of Bovine Milk Somatic Cells.

The production of milk by dairy cows far exceeds the nutritional needs of the calf and is vital for the economical use of dairy cattle. High milk yield is a unique production trait that can be effectively enhanced through traditional selection methods. The process of lactation in cows serves as an excellent model for studying the biological aspects of lactation with the aim of exploring the mechanistic base of this complex trait at the cellular level. In this study, we analyzed the milk transcriptome at the single-cell level by conducting scRNA-seq analysis on milk samples from two Holstein Friesian cows at mid-lactation (75 and 93 days) using the 10× Chromium platform. Cells were pelleted and fat was removed from milk by centrifugation. The cell suspension from each cow was loaded on separate channels, resulting in the recovery of 9313 and 14,544 cells. Library samples were loaded onto two lanes of the NovaSeq 6000 (Illumina) instrument. After filtering at the cell and gene levels, a total of 7988 and 13,973 cells remained, respectively. We were able to reconstruct different cell types (milk-producing cells, progenitor cells, macrophages, monocytes, dendritic cells, T cells, B cells, mast cells, and neutrophils) in bovine milk. Our findings provide a valuable resource for identifying regulatory elements associated with various functions of the mammary gland such as lactation, tissue renewal, native immunity, protein and fat synthesis, and hormonal response.

Identification of Genetic Variants for Risk Prediction and Early Diagnosis of Age-Related Macular Degeneration in the Taiwanese Population.

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly worldwide. The prevalence and phenotypes of AMD differ among populations, including between people in Taiwan and other regions. We performed a genome-wide association study to identify genetic variants and to develop genetic models to predict the risk of AMD development and progression in the Taiwanese population. In total, 4039 patients with AMD and 16,488 non-AMD controls (aged ≥ 65 years) were included. We identified 31 AMD-associated variants (p < 5 × 10-8) on chromosome 10q26, surrounding PLEKHA1-ARMS2-HTRA1. Two genetic models were constructed using the clump and threshold method. Model 1 included the single nucleotide polymorphism rs11200630 and showed a 1.31-fold increase in the risk of AMD per risk allele (95% confidence interval (CI) = 1.20-1.43, p < 0.001). In model 2, 1412 single-nucleotide polymorphisms were selected to construct a polygenic risk score (PRS). Individuals with the top 5% PRS had a 1.40-fold higher AMD risk compared with that of individuals with a PRS in the bottom quartile (95% CI = 1.04-1.89, p = 0.025). Moreover, the PRS in the upper quartile was related to a decreased age at AMD diagnosis by 0.62 years (95% CI = -1.15, -0.09, p = 0.023). Both genetic models provide useful predictive power for populations at high risk of AMD, affording a basis for identifying patients requiring close follow-up and early intervention.

Neuromuscular organoids model spinal neuromuscular pathologies in C9orf72 amyotrophic lateral sclerosis.

Hexanucleotide repeat expansions in the C9orf72 gene are the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Due to the lack of trunk neuromuscular organoids (NMOs) from ALS patients' induced pluripotent stem cells (iPSCs), an organoid system was missing to model the trunk spinal neuromuscular neurodegeneration. With the C9orf72 ALS patient-derived iPSCs and isogenic controls, we used an NMO system containing trunk spinal cord neural and peripheral muscular tissues to show that the ALS NMOs could model peripheral defects in ALS, including contraction weakness, neural denervation, and loss of Schwann cells. The neurons and astrocytes in ALS NMOs manifested the RNA foci and dipeptide repeat proteins. Acute treatment with the unfolded protein response inhibitor GSK2606414 increased the glutamatergic muscular contraction 2-fold and reduced the dipeptide repeat protein aggregation and autophagy. This study provides an organoid system for spinal neuromuscular pathologies in ALS and its application for drug testing.

Sensitive remote homology search by local alignment of small positional embeddings from protein language models.

Accurately detecting distant evolutionary relationships between proteins remains an ongoing challenge in bioinformatics. Search methods based on primary sequence struggle to accurately detect homology between sequences with less than 20% amino acid identity. Profile- and structure-based strategies extend sensitive search capabilities into this twilight zone of sequence similarity but require slow pre-processing steps. Recently, whole-protein and positional embeddings from deep neural networks have shown promise for providing sensitive sequence comparison and annotation at long evolutionary distances. Embeddings are generally faster to compute than profiles and predicted structures but still suffer several drawbacks related to the ability of whole-protein embeddings to discriminate domain-level homology, and the database size and search speed of methods using positional embeddings. In this work, we show that low-dimensionality positional embeddings can be used directly in speed-optimized local search algorithms. As a proof of concept, we use the ESM2 3B model to convert primary sequences directly into the 3D interaction (3Di) alphabet or amino acid profiles and use these embeddings as input to the highly optimized Foldseek, HMMER3, and HH-suite search algorithms. Our results suggest that positional embeddings as small as a single byte can provide sufficient information for dramatically improved sensitivity over amino acid sequence searches without sacrificing search speed.

GO2Sum: generating human-readable functional summary of proteins from GO terms.

Understanding the biological functions of proteins is of fundamental importance in modern biology. To represent a function of proteins, Gene Ontology (GO), a controlled vocabulary, is frequently used, because it is easy to handle by computer programs avoiding open-ended text interpretation. Particularly, the majority of current protein function prediction methods rely on GO terms. However, the extensive list of GO terms that describe a protein function can pose challenges for biologists when it comes to interpretation. In response to this issue, we developed GO2Sum (Gene Ontology terms Summarizer), a model that takes a set of GO terms as input and generates a human-readable summary using the T5 large language model. GO2Sum was developed by fine-tuning T5 on GO term assignments and free-text function descriptions for UniProt entries, enabling it to recreate function descriptions by concatenating GO term descriptions. Our results demonstrated that GO2Sum significantly outperforms the original T5 model that was trained on the entire web corpus in generating Function, Subunit Structure, and Pathway paragraphs for UniProt entries.

Association of a single-nucleotide polymorphism in C12orf43 region with the risk of coronary artery disease.

The genetics of organisms play a vital role in the development of coronary artery disease (CAD), with its heritability estimated at approximately 50-60%. For this purpose, we examined the relationship between CAD risk and C12orf43/rs2258287 polymorphisms in the Pakistani population. In this study based on the genetic approach to dyslipidemia, a total of 200 subjects were included from the southern Punjab. The biochemical analysis of parameters (total cholesterol, triglycerides, blood glucose, high-density lipoprotein, and low-density lipoprotein) was carried out along with molecular analysis using an ARMS-PCR-based assay for single-nucleotide polymorphism (SNP) C12orf43/rs2258287 to identify the genotype. Genotypes showed a substantial correlation with both family history and metabolic markers. The cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides and blood glucose levels were higher while the high-density lipoprotein cholesterol (HDL-C) level was lower significantly (p<0.05) in cases than in controls. Age, pulse rate, diabetes, physical activity, smoking, family history, and dietary habits were also significantly associated (p<0.05) with CAD individuals. The SNP C12orf43/rs2258287 also showed an association with CAD in the population of southern Punjab. Based upon this study, it could be concluded that CAD is characterized by an unfavorable lipid profile in association with SNP C12orf43/rs2258287.

The pathogenic roles of the p.R130S prestin variant in DFNB61 hearing loss.

DFNB61 is a recessively inherited nonsyndromic hearing loss caused by mutations in SLC26A5, the gene that encodes the voltage-driven motor protein, prestin. Prestin is abundantly expressed in the auditory outer hair cells that mediate cochlear amplification. Two DFNB61-associated SLC26A5 variants, p.W70X and p.R130S, were identified in patients who are compound heterozygous for these nonsense and missense changes (SLC26A5W70X/R130S ). Our recent study showed that mice homozygous for p.R130S (Slc26a5R130S/R130S ) suffer from hearing loss that is ascribed to significantly reduced motor kinetics of prestin. Given that W70X-prestin is nonfunctional, compound heterozygous Slc26a5R130S/- mice were used as a model for human SLC26A5W70X/R130S . By examining the pathophysiological consequences of p.R130S prestin when it is the sole allele for prestin protein production, we determined that this missense change results in progressive outer hair cell loss in addition to its effects on prestin's motor action. Thus, this study defines the pathogenic roles of p.R130S prestin and identifies a limited time window for potential clinical intervention. KEY POINTS: The voltage-driven motor protein, prestin, is encoded by SLC26A5 and expressed abundantly in cochlear outer hair cells (OHCs). The importance of prestin for normal hearing was demonstrated in mice lacking prestin; however, none of the specific SLC26A5 variants identified to date in human patients has been experimentally demonstrated to be pathogenic. In this study we used both cell lines and a mouse model to define the pathogenic role of compound heterozygous p.W70X (c.209G>A) and p.R130S (c.390A>C) SLC26A5 variants identified in patients with moderate to profound hearing loss. As in patients, mice carrying one copy of p.R130S Slc26a5 showed OHC dysfunction and progressive degeneration, which results in congenital progressive hearing loss. This is the first functional study reporting pathogenic SLC26A5 variants and pointing to the presence of a therapeutic time window for potential clinical interventions targeting the affected OHCs before they are lost.

Exact p-values for global network alignments via combinatorial analysis of shared GO terms : REFANGO: Rigorous Evaluation of Functional Alignments of Networks using Gene Ontology.

Network alignment aims to uncover topologically similar regions in the protein-protein interaction (PPI) networks of two or more species under the assumption that topologically similar regions tend to perform similar functions. Although there exist a plethora of both network alignment algorithms and measures of topological similarity, currently no "gold standard" exists for evaluating how well either is able to uncover functionally similar regions. Here we propose a formal, mathematically and statistically rigorous method for evaluating the statistical significance of shared GO terms in a global, 1-to-1 alignment between two PPI networks. Given an alignment in which k aligned protein pairs share a particular GO term g, we use a combinatorial argument to precisely quantify the p-value of that alignment with respect to g compared to a random alignment. The p-value of the alignment with respect to all GO terms, including their inter-relationships, is approximated using the Empirical Brown's Method. We note that, just as with BLAST's p-values, this method is not designed to guide an alignment algorithm towards a solution; instead, just as with BLAST, an alignment is guided by a scoring matrix or function; the p-values herein are computed after the fact, providing independent feedback to the user on the biological quality of the alignment that was generated by optimizing the scoring function. Importantly, we demonstrate that among all GO-based measures of network alignments, ours is the only one that correlates with the precision of GO annotation predictions, paving the way for network alignment-based protein function prediction.

Gene dosage of independent dynein arm motor preassembly factors influences cilia assembly in Chlamydomonas reinhardtii.

Motile cilia assembly utilizes over 800 structural and cytoplasmic proteins. Variants in approximately 58 genes cause primary ciliary dyskinesia (PCD) in humans, including the dynein arm (pre)assembly factor (DNAAF) gene DNAAF4. In humans, outer dynein arms (ODAs) and inner dynein arms (IDAs) fail to assemble motile cilia when DNAAF4 function is disrupted. In Chlamydomonas reinhardtii, a ciliated unicellular alga, the DNAAF4 ortholog is called PF23. The pf23-1 mutant assembles short cilia and lacks IDAs, but partially retains ODAs. The cilia of a new null allele (pf23-4) completely lack ODAs and IDAs and are even shorter than cilia from pf23-1. In addition, PF23 plays a role in the cytoplasmic modification of IC138, a protein of the two-headed IDA (I1/f). As most PCD variants in humans are recessive, we sought to test if heterozygosity at two genes affects ciliary function using a second-site non-complementation (SSNC) screening approach. We asked if phenotypes were observed in diploids with pairwise heterozygous combinations of 21 well-characterized ciliary mutant Chlamydomonas strains. Vegetative cultures of single and double heterozygous diploid cells did not show SSNC for motility phenotypes. When protein synthesis is inhibited, wild-type Chlamydomonas cells utilize the pool of cytoplasmic proteins to assemble half-length cilia. In this sensitized assay, 8 double heterozygous diploids with pf23 and other DNAAF mutations show SSNC; they assemble shorter cilia than wild-type. In contrast, double heterozygosity of the other 203 strains showed no effect on ciliary assembly. Immunoblots of diploids heterozygous for pf23 and wdr92 or oda8 show that PF23 is reduced by half in these strains, and that PF23 dosage affects phenotype severity. Reductions in PF23 and another DNAAF in diploids affect the ability to assemble ODAs and IDAs and impedes ciliary assembly. Thus, dosage of multiple DNAAFs is an important factor in cilia assembly and regeneration.