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.

In silico identification and expression analyses of peroxidases in Tenebrio molitor

Human advancements in agriculture, urbanization, and industrialization have led to various forms of environmental pollution, including heavy metal pollution. Insects, as highly adaptable organisms, can survive under various environmental stresses, which induce oxidative damage and impair antioxidant systems. To investigate the peroxidase (POX) family in Tenebrio molitor, we characterized two POXs, namely TmPOX-iso1 and TmPOX-iso2. The full-length cDNA sequences of TmPox-iso1 and TmPox-iso2 respectively consisted of an open reading frame of 1815 bp encoding 605 amino acids and an open reading frame of 2229 bp encoding 743 amino acids. TmPOX-iso1 and TmPOX-iso2 homologs were found in five distinct insect orders. In the phylogenetic tree analysis, TmPOX-iso1 was clustered with the predicted POX protein of T. castaneum, and TmPOX-iso2 was clustered with the POX precursor protein of T. castaneum. During development, the highest expression level of TmPox-iso1 was observed in the pre-pupal stage, while that of TmPox-iso2 expression were observed in the pre-pupal and 4-day pupal stages. TmPox-iso1 was primarily expressed in the early and late larval gut, while TmPox-iso2 mRNA expression was higher in the fat bodies and Malpighian tubules. In response to cadmium chloride treatment, TmPox-iso1 expression increased at 3 hours and then declined until 24 hours, while in the zinc chloride-treated group, TmPox-iso1 expression peaked 24 hours after the treatment. Both treated groups showed increases in TmPox-iso2 expression 24 hours after the treatments.

Sequence-dependent and -independent information in a combined random energy model for protein folding and coding

Random energy models (REMs) provide a simple description of the energy landscapes that guide protein folding and evolution. The requirement of a large energy gap between the native structure and unfolded conformations, considered necessary for cooperative, protein-like, folding behavior, indicates that proteins differ markedly from random heteropolymers. It has been suggested, therefore, that natural selection might have acted to choose nonrandom amino acid sequences satisfying this particular condition, implying that a large fraction of possible, unselected random sequences, would not fold to any structure. From an informational perspective, however, this scenario could indicate that protein structures, regarded as messages to be transmitted through a communication channel, would not be efficiently encoded in amino acid sequences, regarded as the communication channel for this transmission, since a large fraction of possible channel states would not be used. Here, we use a combined REM for conformations and sequences, with previously estimated parameters for natural proteins, to explore an alternative possibility in which the appropriate shape of the landscape results mainly from the deviation from randomness of possible native structures instead of sequences. We observe that this situation emerges naturally if the distribution of conformational energies happens to arise from two independent contributions corresponding to sequence-dependent and -independent terms. This construction is consistent with the hypothesis of a protein burial folding code, with native structures being determined by a modest amount of sequence-dependent atomic burial information with sequence-independent constraints imposed by unspecific hydrogen bond formation. More generally, an appropriate combination of sequence-dependent and -independent information accommodates the possibility of an efficient structural encoding with the main physical requirement for folding, providing possible insight not only on the folding process but also on several aspects sequence evolution such as neutral networks, conformational coverage, and de novo gene emergence.

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.

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.

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.

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.

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.

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.

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.

Extant Sequence Reconstruction: The Accuracy of Ancestral Sequence Reconstructions Evaluated by Extant Sequence Cross-Validation

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term "extant sequence reconstruction" (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

Translation machinery: the basis of translational control

Messenger RNA (mRNA) translation consists of initiation, elongation, termination, and ribosome recycling, carried out by the translation machinery, primarily including tRNAs, ribosomes, and translation factors (TrFs). Translational regulators transduce signals of growth and development, as well as biotic and abiotic stresses, to the translation machinery, where global or selective translational control occurs to modulate mRNA translation efficiency (TrE). As the basis of translational control, the translation machinery directly determines the quality and quantity of newly synthesized peptides and, ultimately, the cellular adaption. Thus, regulating the availability of diverse machinery components is reviewed as the central strategy of translational control. We provide classical signaling pathways (e.g., integrated stress responses) and cellular behaviors (e.g., liquid-liquid phase separation) to exemplify this strategy within different physiological contexts, particularly during host-microbe interactions. With new technologies developed, further understanding this strategy will speed up translational medicine and translational agriculture.

Evolution of Transcript Abundance is Influenced by Indels in Protein Low Complexity Regions

Protein Protein low complexity regions (LCRs) are compositionally biased amino acid sequences, many of which have significant evolutionary impacts on the proteins which contain them. They are mutationally unstable experiencing higher rates of indels and substitutions than higher complexity regions. LCRs also impact the expression of their proteins, likely through multiple effects along the path from gene transcription, through translation, and eventual protein degradation. It has been observed that proteins which contain LCRs are associated with elevated transcript abundance (TAb), despite having lower protein abundance. We have gathered and integrated human data to investigate the co-evolution of TAb and LCRs through ancestral reconstructions and model inference using an approximate Bayesian calculation based method. We observe that on short evolutionary timescales TAb evolution is significantly impacted by changes in LCR length, with insertions driving TAb down. But in contrast, the observed data is best explained by indel rates in LCRs which are unaffected by shifts in TAb. Our work demonstrates a coupling between LCR and TAb evolution, and the utility of incorporating multiple responses into evolutionary analyses.

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

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.

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.

Single-sequence protein structure prediction by integrating protein language models

Protein structure prediction has been greatly improved by deep learning in the past few years. However, the most successful methods rely on multiple sequence alignment (MSA) of the sequence homologs of the protein under prediction. In nature, a protein folds in the absence of its sequence homologs and thus, a MSA-free structure prediction method is desired. Here, we develop a single-sequence-based protein structure prediction method RaptorX-Single by integrating several protein language models and a structure generation module and then study its advantage over MSA-based methods. Our experimental results indicate that in addition to running much faster than MSA-based methods such as AlphaFold2, RaptorX-Single outperforms AlphaFold2 and other MSA-free methods in predicting the structure of antibodies (after fine-tuning on antibody data), proteins of very few sequence homologs, and single mutation effects. By comparing different protein language models, our results show that not only the scale but also the training data of protein language models will impact the performance. RaptorX-Single also compares favorably to MSA-based AlphaFold2 when the protein under prediction has a large number of sequence homologs.

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.

Novel TFG mutation causes autosomal-dominant spastic paraplegia and defects in autophagy

BACKGROUND

Mutations in the tropomyosin receptor kinase fused (TFG) gene are associated with various neurological disorders, including autosomal recessive hereditary spastic paraplegia (HSP), autosomal dominant hereditary motor and sensory neuropathy with proximal dominant involvement (HMSN-P) and autosomal dominant type of Charcot-Marie-Tooth disease type 2.

METHODS

Whole genome sequencing and whole-exome sequencing were used, followed by Sanger sequencing for validation. Haplotype analysis was performed to confirm the inheritance mode of the novel TFG mutation in a large Chinese family with HSP. Additionally, another family diagnosed with HMSN-P and carrying the reported TFG mutation was studied. Clinical data and muscle pathology comparisons were drawn between patients with HSP and patients with HMSN-P. Furthermore, functional studies using skin fibroblasts derived from patients with HSP and patients with HMSN-P were conducted to investigate the pathomechanisms of TFG mutations.

RESULTS

A novel heterozygous TFG variant (NM_006070.6: c.125G>A (p.R42Q)) was identified and caused pure HSP. We further confirmed that the well-documented recessively inherited spastic paraplegia, caused by homozygous TFG mutations, exists in a dominantly inherited form. Although the clinical features and muscle pathology between patients with HSP and patients with HMSN-P were distinct, skin fibroblasts derived from both patient groups exhibited reduced levels of autophagy-related proteins and the presence of TFG-positive puncta.

CONCLUSIONS

Our findings suggest that autophagy impairment may serve as a common pathomechanism among different clinical phenotypes caused by TFG mutations. Consequently, targeting autophagy may facilitate the development of a uniform treatment for TFG-related neurological disorders.

piRNA generation is associated with the pioneer round of translation in stem cells

Much insight has been gained on how stem cells maintain genomic integrity, but less attention has been paid to how they maintain their transcriptome. Here, we report that the PIWI protein SMEDWI-1 plays a role in the filtering of dysfunctional transcripts from the transcriptome of planarian stem cells. SMEDWI-1 accomplishes this through association with the ribosomes during the pioneer round of translation, and processing of poorly translated transcripts into piRNAs. This results in the removal of such transcripts from the cytoplasmic pool and at the same time creates a dynamic pool of small RNAs for post-transcriptional surveillance through the piRNA pathway. Loss of SMEDWI-1 results in elevated levels of several non-coding transcripts, including rRNAs, snRNAs and pseudogene mRNAs, while reducing levels of several coding transcripts. In the absence of SMEDWI-1, stem cell colonies are delayed in their expansion and a higher fraction of descendants exit the stem cell state, indicating that this transcriptomic sanitation mediated by SMEDWI-1 is essential to maintain stem cell health. This study presents a new model for the function of PIWI proteins in stem cell maintenance, that complements their role in transposon repression, and proposes a new biogenesis pathway for piRNAs in stem cells.

Clinical and molecular heterogeneity of VPS13D-related neurodevelopmental and movement disorders

BACKGROUND

The VPS13 family of proteins has been implicated in lipid transport and trafficking between endoplasmic reticulum and organelles, to maintain homeostasis of subcellular membranes. Recently, pathogenic variants in each human VPS13S gene, have been linked to distinct human neurodevelopmental or neurodegenerative disorders. Within the VPS13 family of genes, VPS13D is known to be implicated in mitochondria homeostasis and function.

METHODS

We investigated a Pakistani sibship affected with neurodevelopmental impairment and severe hyperkinetic (choreoathetoid) movements. Whole exome sequencing (WES) and Sanger sequencing were performed to identify potential candidate variants segregating in the family. We described clinical phenotypes and natural history of the disease during a 3-year clinical follow-up and summarized literature data related to previously identified patients with VPS13D-related neurological disorders.

RESULTS

We identified by WES an homozygous non-synonymous variant in VPS13D (c.5723 T > C; p.Ile1908Thr) as the potential underlying cause of the disease in our family. Two young siblings developed an early-onset neurological impairment characterized by global developmental delay, with impaired speech and motor milestones, associated to hyperkinetic movement disorders as well as progressive and non-progressive neurological abnormalities.

CONCLUSION

In this study we delineated the heterogeneity of VPS13D-related clinical phenotypes and described a novel VPS13D homozygous variant associated with severe neurological impairment. Further studies will be pivotal to understand the exact VPS13D function and its impact on mitochondria homeostasis, brain development and regulation of movements, to further clarify genotype-phenotype correlations and provide crucial prognostic information and potential therapeutic implications.

Preferential formation of Z-RNA over intercalated motifs in long noncoding RNA

Secondary structure is a principal determinant of lncRNA function, predominantly regarding scaffold formation and interfaces with target molecules. Noncanonical secondary structures that form in nucleic acids have known roles in regulating gene expression and include G-quadruplexes (G4s), intercalated motifs (iMs), and R-loops (RLs). In this paper, we used the computational tools G4-iM Grinder and QmRLFS-finder to predict the formation of each of these structures throughout the lncRNA transcriptome in comparison to protein-coding transcripts. The importance of the predicted structures in lncRNAs in biological contexts was assessed by combining our results with publicly available lncRNA tissue expression data followed by pathway analysis. The formation of predicted G4 (pG4) and iM (piM) structures in select lncRNA sequences was confirmed in vitro using biophysical experiments under near-physiological conditions. We find that the majority of the tested pG4s form highly stable G4 structures, and identify many previously unreported G4s in biologically important lncRNAs. In contrast, none of the piM sequences are able to form iM structures, consistent with the idea that RNA is unable to form stable iMs. Unexpectedly, these C-rich sequences instead form Z-RNA structures, which have not been previously observed in regions containing cytosine repeats and represent an interesting and underexplored target for protein-RNA interactions. Our results highlight the prevalence and potential structure-associated functions of noncanonical secondary structures in lncRNAs, and show G4 and Z-RNA structure formation in many lncRNA sequences for the first time, furthering the understanding of the structure-function relationship in lncRNAs.

Reconstitution of the antagonistic effect between C1orf112/FIRRM-FIGNL1 and BRCA2 on RAD51 filament stabilization

C1orf112/FIRRM is a recently identified DNA damage repair factor that regulates RAD51 in homologous recombination through interacting with the anti-recombinase FIGNL1. Here, we describe steps for purifying C1orf112/FIRRM, FIGNL1, miBRCA2, and RAD51 proteins from Escherichia coli or Saccharomyces cerevisiae cells. We then detail procedures for reconstituting the disassembly of RAD51 filament by C1orf112/FIRRM-FIGNL1 in vitro and the antagonistic effect between C1orf112/FIRRM-FIGNL1 and miBRCA2 on RAD51 filament stabilization. For complete details on the use and execution of this protocol, please refer to Zhou et al. (2023).1.

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.

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.

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.

Genetic associations with ratios between protein levels detect new pQTLs and reveal protein-protein interactions

Protein quantitative trait loci (pQTLs) are an invaluable source of information for drug target development because they provide genetic evidence to support protein function, suggest relationships between cis- and trans-associated proteins, and link proteins to disease endpoints. Using Olink proteomics data for 1,463 proteins measured in over 54,000 samples of the UK Biobank, we identified 4,248 associations with 2,821 ratios between protein levels (rQTLs). rQTLs were 7.6-fold enriched in known protein-protein interactions, suggesting that their ratios reflect biological links between the implicated proteins. Conducting a GWAS on ratios increased the number of discovered genetic signals by 24.7%. The approach can identify novel loci of clinical relevance, support causal gene identification, and reveal complex networks of interacting proteins. Taken together, our study adds significant value to the genetic insights that can be derived from the UKB proteomics data and motivates the wider use of ratios in large-scale GWAS.

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.

Analysis of C9orf72 repeat expansions in Georgian patients with Amyotrophic lateral sclerosis (ALS)

Background

Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disorder that affects the upper and lower motor neurons. Several genetic risk factors have been identified in the past decade with a hexanucleotide repeat expansion in the C9orf72 gene being the most significant. However, the presence of C9orf72 repeat expansion has not been examined in the Transcaucasian region, therefore we aimed to analyse its frequency in Georgian patients with ALS.

Methods

We included 64 self-reported Georgian patients with ALS from different parts of the country, fulfilling the Gold Coast criteria. To investigate the presence of an expanded GGGGCC hexanucleotide repeat in the non-coding region of the C9orf72 gene, we performed Repeat-Primed PCR (RP-PCR).

Results

In total, 62 sporadic and two familial ALS cases were identified. Patients were aged 26 to 84 years with a mean age of 58.3 years at disease onset. Bulbar onset was observed in 21.88%, upper limb onset in 34.38%, and lower limb onset in 43.75% of the patients. Frontotemporal dementia (FTD) fulfilling the Strong criteria was diagnosed in seven patients (10.94%). C9orf72 repeat expansion was detected in only one case using RP-PCR; the patient had a family history of dementia.

Conclusions

Our results indicate that C9orf72 hexanucleotide expansion does not belong to the major genetic risk factor of ALS in Georgian patients. Further genetic studies in a bigger study population are needed to reveal the genetic causes of ALS in the Transcaucasian population.

A billion years of evolution manifest in nanosecond protein dynamics

Protein dynamics form a critical bridge between protein structure and function, yet the impact of evolution on ultrafast processes inside proteins remains enigmatic. This study delves deep into nanosecond-scale protein dynamics of a structurally and functionally conserved protein across species separated by almost a billion years, investigating ten homologs in complex with their ligand. By inducing a photo-triggered destabilization of the ligand inside the binding pocket, we resolved distinct kinetic footprints for each homolog via transient infrared spectroscopy. Strikingly, we found a cascade of rearrangements within the protein complex which manifest in time points of increased dynamic activity conserved over hundreds of millions of years within a narrow window. Among these processes, one displays a subtle temporal shift correlating with evolutionary divergence, suggesting reduced selective pressure in the past. Our study not only uncovers the impact of evolution on molecular processes in a specific case, but has also the potential to initiate a field of scientific inquiry within molecular paleontology, where species are compared and classified based on the rapid pace of protein dynamic processes; a field which connects the shortest conceivable time scale in living matter (10[Formula: see text] s) with the largest ones (10[Formula: see text] s).

Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation

MOTIVATION

The selection among substitution models of molecular evolution is fundamental for obtaining accurate phylogenetic inferences. At the protein level, evolutionary analyses are traditionally based on empirical substitution models but these models make unrealistic assumptions and are being surpassed by structurally constrained substitution (SCS) models. The SCS models often consider site-dependent evolution, a process that provides realism but complicates their implementation into likelihood functions that are commonly used for substitution model selection.

RESULTS

We present a method to perform selection among site-dependent SCS models, also among empirical and site-dependent SCS models, based on the approximate Bayesian computation (ABC) approach and its implementation into the computational framework ProteinModelerABC. The framework implements ABC with and without regression adjustments and includes diverse empirical and site-dependent SCS models of protein evolution. Using extensive simulated data, we found that it provides selection among SCS and empirical models with acceptable accuracy. As illustrative examples, we applied the framework to analyze a variety of protein families observing that SCS models fit them better than the corresponding best-fitting empirical substitution models.

AVAILABILITY AND IMPLEMENTATION

ProteinModelerABC is freely available from https://github.com/DavidFerreiro/ProteinModelerABC, can run in parallel and includes a graphical user interface. The framework is distributed with detailed documentation and ready-to-use examples.

Pooled CRISPR Screening Identifies P-Bodies as Repressors of Cancer Epithelial-Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a fundamental cellular process frequently hijacked by cancer cells to promote tumor progression, especially metastasis. EMT is orchestrated by a complex molecular network acting at different layers of gene regulation. In addition to transcriptional regulation, posttranscriptional mechanisms may also play a role in EMT. Here, we performed a pooled CRISPR screen analyzing the influence of 1,547 RNA-binding proteins on cell motility in colon cancer cells and identified multiple core components of P-bodies (PB) as negative modulators of cancer cell migration. Further experiments demonstrated that PB depletion by silencing DDX6 or EDC4 could activate hallmarks of EMT thereby enhancing cell migration in vitro as well as metastasis formation in vivo. Integrative multiomics analysis revealed that PBs could repress the translation of the EMT driver gene HMGA2, which contributed to PB-meditated regulation of EMT. This mechanism is conserved in other cancer types. Furthermore, endoplasmic reticulum stress was an intrinsic signal that induced PB disassembly and translational derepression of HMGA2. Taken together, this study has identified a function of PBs in the regulation of EMT in cancer.

SIGNIFICANCE

Systematic investigation of the influence of posttranscriptional regulation on cancer cell motility established a connection between P-body-mediated translational control and EMT, which could be therapeutically exploited to attenuate metastasis formation.

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.

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.

Rheostats, toggles, and neutrals, Oh my! A new framework for understanding how amino acid changes modulate protein function

Advances in personalized medicine and protein engineering require accurately predicting outcomes of amino acid substitutions. Many algorithms correctly predict that evolutionarily-conserved positions show "toggle" substitution phenotypes, which is defined when a few substitutions at that position retain function. In contrast, predictions often fail for substitutions at the less-studied "rheostat" positions, which are defined when different amino acid substitutions at a position sample at least half of the possible functional range. This review describes efforts to understand the impact and significance of rheostat positions: (1) They have been observed in globular soluble, integral membrane, and intrinsically disordered proteins; within single proteins, their prevalence can be up to 40%. (2) Substitutions at rheostat positions can have biological consequences and ∼10% of substitutions gain function. (3) Although both rheostat and "neutral" (defined when all substitutions exhibit wild-type function) positions are nonconserved, the two classes have different evolutionary signatures. (4) Some rheostat positions have pleiotropic effects on function, simultaneously modulating multiple parameters (e.g., altering both affinity and allosteric coupling). (5) In structural studies, substitutions at rheostat positions appear to cause only local perturbations; the overall conformations appear unchanged. (6) Measured functional changes show promising correlations with predicted changes in protein dynamics; the emergent properties of predicted, dynamically coupled amino acid networks might explain some of the complex functional outcomes observed when substituting rheostat positions. Overall, rheostat positions provide unique opportunities for using single substitutions to tune protein function. Future studies of these positions will yield important insights into the protein sequence/function relationship.

Systematic enhancement of protein crystallization efficiency by bulk lysine-to-arginine (KR) substitution

Structural genomics consortia established that protein crystallization is the primary obstacle to structure determination using x-ray crystallography. We previously demonstrated that crystallization propensity is systematically related to primary sequence, and we subsequently performed computational analyses showing that arginine is the most overrepresented amino acid in crystal-packing interfaces in the Protein Data Bank. Given the similar physicochemical characteristics of arginine and lysine, we hypothesized that multiple lysine-to-arginine (KR) substitutions should improve crystallization. To test this hypothesis, we developed software that ranks lysine sites in a target protein based on the redundancy-corrected KR substitution frequency in homologs. This software can be run interactively on the worldwide web at https://www.pxengineering.org/. We demonstrate that three unrelated single-domain proteins can tolerate 5-11 KR substitutions with at most minor destabilization, and, for two of these three proteins, the construct with the largest number of KR substitutions exhibits significantly enhanced crystallization propensity. This approach rapidly produced a 1.9 Å crystal structure of a human protein domain refractory to crystallization with its native sequence. Structures from Bulk KR-substituted domains show the engineered arginine residues frequently make hydrogen-bonds across crystal-packing interfaces. We thus demonstrate that Bulk KR substitution represents a rational and efficient method for probabilistic engineering of protein surface properties to improve crystallization.

Ubiquitination and deubiquitination in the regulation of N6-methyladenosine functional molecules

N6 methyladenosine (m6A) is the most prevalent RNA epigenetic modification, regulated by methyltransferases and demethyltransferases and recognized by methylation-related reading proteins to impact mRNA splicing, translocation, stability, and translation efficiency. It significantly affects a variety of activities, including stem cell maintenance and differentiation, tumor formation, immune regulation, and metabolic disorders. Ubiquitination refers to the specific modification of target proteins by ubiquitin molecule in response to a series of enzymes. E3 ligases connect ubiquitin to target proteins and usually lead to protein degradation. On the contrary, deubiquitination induced by deubiquitinating enzymes (DUBs) can separate ubiquitin and regulate the stability of protein. Recent studies have emphasized the potential importance of ubiquitination and deubiquitination in controlling the function of m6A modification. In this review, we discuss the impact of ubiquitination and deubiquitination on m6A functional molecules in diseases, such as metabolism, cellular stress, and tumor growth.

Prioritising genetic findings for drug target identification and validation

The decreasing costs of high-throughput genetic sequencing and increasing abundance of sequenced genome data have paved the way for the use of genetic data in identifying and validating potential drug targets. However, the number of identified potential drug targets is often prohibitively large to experimentally evaluate in wet lab experiments, highlighting the need for systematic approaches for target prioritisation. In this review, we discuss principles of genetically guided drug development, specifically addressing loss-of-function analysis, colocalization and Mendelian randomisation (MR), and the contexts in which each may be most suitable. We subsequently present a range of biomedical resources which can be used to annotate and prioritise disease-associated proteins identified by these studies including 1) ontologies to map genes, proteins, and disease, 2) resources for determining the druggability of a potential target, 3) tissue and cell expression of the gene encoding the potential target, and 4) key biological pathways involving the potential target. We illustrate these concepts through a worked example, identifying a prioritised set of plasma proteins associated with non-alcoholic fatty liver disease (NAFLD). We identified five proteins with strong genetic support for involvement with NAFLD: CYB5A, NT5C, NCAN, TGFBI and DAPK2. All of the identified proteins were expressed in both liver and adipose tissues, with TGFBI and DAPK2 being potentially druggable. In conclusion, the current review provides an overview of genetic evidence for drug target identification, and how biomedical databases can be used to provide actionable prioritisation, fully informing downstream experimental validation.

Major Histocompatibility Complex II Expression on Oral Langerhans Cells Differentially Regulates Mucosal CD4 and CD8 T Cells

In murine periodontitis, the T helper (Th)17 response against Porphyromonas gingivalis in cervical lymph node is abrogated by diphtheria toxin-driven depletion of Langerhans cells (LCs). We determined the impact of major histocompatibility complex class II (MHC-II) presentation in LCs on Th17 cells in the oral mucosa of mice. Using an established human-Langerin promoter-Cre mouse model, we generated LC-specific deletion of the H2-Ab1 (MHC-II) gene. MHC-II expression was ablated in 81.2% of oral-resident LCs compared with >99% of skin-resident LCs. MHC-II (LCΔMHC-II) depletion did not reduce the number of CD4 T cells nor the frequency of Th17 cells compared with that in wild-type mice. However, the frequencies of Th1 cells decreased, and Helios+ T-regulatory cells increased. In ligature-induced periodontitis, the numbers of CD4 T cells and Th17 cells were similar in LCΔMHC-II and wild-type mice. Normal numbers of Th17 cells can therefore be sustained by as little as 18.8% of MHC-II-expressing LCs in oral mucosa. Unexpectedly, oral mucosa CD8 T cells increased >25-fold in LCΔMHC-II mice. Hence, these residual MHC-II-expressing LCs appear unable to suppress the local expansion of CD8 T cells while sufficient to sustain a homeostatic CD4 T-cell response. Reducing the expression of MHC-II on specific LC subpopulations may ultimately boost CD8-mediated intraepithelial surveillance at mucosal surfaces.

Codon usage bias and phylogenetic analysis of chloroplast genome in 36 gracilariaceae species

Gracilariaceae is a group of marine large red algae and main source of agar with important economic and ecological value. The codon usage patterns of chloroplast genomes in 36 species from Graciliaceae show that GC range from 0.284 to 0.335, the average GC3 range from 0.135 to 0.243 and the value of ENC range from 35.098 to 42.327, which indicates these genomes are rich in AT and prefer to use codons ending with AT in these species. Nc plot, PR2 plot, neutrality plot analyses and correlation analysis indicate that these biases may be caused by multiple factors, such as natural selection and mutation pressure, but prolonged natural selection is the main driving force influencing codon usage preference. The cluster analysis and phylogenetic analysis show that the differentiation relationship of them is different and indicate that codons with weak or unbiased preferences may also play an irreplaceable role in these species' evolution. In addition, we identified 26 common high-frequency codons and 8-18 optimal codons all ending in A/U in these 36 species. Our results will not only contribute to carrying out transgenic work in Gracilariaceae species to maximize the protein yield in the future, but also lay a theoretical foundation for further exploring systematic classification of them.

A Retrospective Review of 18 Patients With Childhood-Onset Hereditary Spastic Paraplegia, Nine With Novel Variants

BACKGROUND

Hereditary spastic paraplegias (HSPs) are a group of genetically heterogeneous neurodegenerative disorders. Our objective was to determine the clinical and molecular characteristics of patients with genetically confirmed childhood-onset HSPs and to expand the genetic spectrum for some rare subtypes of HSP.

METHODS

We reviewed the charts of subjects with genetically confirmed childhood-onset HSP. The age at the disease onset was defined as the point at which the delayed motor milestones were observed. Delayed motor milestones were defined as being unable to hold the head up by four months, sitting unassisted by nine months, and walking independently by 17 months. If there were no delayed motor milestones, age at disease onset was determined by leg stiffness, frequent falls, or unsteady gait. Genetic testing was performed based on delayed motor milestones, progressive leg spasticity, and gait difficulty. The variant classification was determined based on the American College of Medical Genetics standard guidelines for variant interpretation. Variants of uncertain significance (VUS) were considered disease-associated when clinical findings were consistent with the previously described disease phenotypes for pathogenic variants. In addition, in the absence of another pathogenic, likely pathogenic, or VUS variant that could explain the phenotype of our cases, we concluded that the disease is associated with VUS in the HSP-causing gene. Segregation analysis was also performed on the parents of some patients to demonstrate the inheritance model.

RESULTS

There were a total of 18 patients from 17 families. The median age of symptom onset was 18 months (2 to 84 months). The mean delay between symptom onset and genetic diagnosis was 5.8 years (5 months to 17 years). All patients had gait difficulty caused by progressive leg spasticity and weakness. Independent walking was not achieved at 17 months for 67% of patients (n = 12). In our cohort, there were two subjects each with SPG11, SPG46, and SPG 50 followed by single subject each with SPG3A, SPG4, SPG7, SPG8, SPG30, SPG35, SPG43, SPG44, SPG57, SPG62, infantile-onset ascending spastic paralysis (IAHSP), and spastic paraplegia and psychomotor retardation with or without seizures (SPPRS). Eight novel variants in nine patients were described. Two affected siblings had a novel variant in the GBA2 gene (SPG46), and one subject each had a novel variant in WASHC5 (SPG8), SPG11 (SPG11), KIF1A (SPG30), GJC2 (SPG44), ERLIN1 (SPG62), ALS2 (IAHSP), and HACE1 (SPPRS). Among the novel variants, the variant in the SPG11 was pathogenic and the variants in the KIF1A, GJC2, and HACE1 were likely pathogenic. The variants in the GBA2, ALS2, ERLIN1, and WASHC5 were classified as VUS.

CONCLUSIONS

There was a significant delay between symptom onset and genetic diagnosis of HSP. An early diagnosis may be possible by examining patients with delayed motor milestones, progressive spasticity, gait difficulties, and neuromuscular weakness in the context of HSP. Eight novel variants in nine patients were described, clinically similar to the previously described disease phenotype associated with pathogenic variants. This study contributes to expanding the genetic spectrum of some rare subtypes of HSP.

Artificial microRNA suppresses C9ORF72 variants and decreases toxic dipeptide repeat proteins in vivo

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that affects motor neurons, causing progressive muscle weakness and respiratory failure. The presence of an expanded hexanucleotide repeat in chromosome 9 open reading frame 72 (C9ORF72) is the most frequent mutation causing familial ALS and frontotemporal dementia (FTD). To determine if suppressing expression of C9ORF72 gene products can reduce toxicity, we designed a set of artificial microRNAs (amiRNA) targeting the human C9ORF72 gene. Here we report that an AAV9-mediated amiRNA significantly suppresses expression of the C9ORF72 mRNA, protein, and toxic dipeptide repeat proteins generated by the expanded repeat in the brain and spinal cord of C9ORF72 transgenic mice.

Resting-state fMRI functional connectome of C9orf72 mutation status

OBJECTIVE

The resting-state functional connectome has not been extensively investigated in amyotrophic lateral sclerosis (ALS) spectrum disease, in particular in relationship with patients' genetic status.

METHODS

Here we studied the network-to-network connectivity of 19 ALS patients carrying the C9orf72 hexanucleotide repeat expansion (C9orf72+), 19 ALS patients not affected by C9orf72 mutation (C9orf72-), and 19 ALS-mimic patients (ALSm) well-matched for demographic and clinical variables.

RESULTS

When compared with ALSm, we observed greater connectivity of the default mode and frontoparietal networks with the visual network for C9orf72+ patients (P = 0.001). Moreover, the whole-connectome showed greater node degree (P < 0.001), while sensorimotor cortices resulted isolated in C9orf72+.

INTERPRETATION

Our results suggest a crucial involvement of extra-motor functions in ALS spectrum disease. In particular, alterations of the visual cortex may have a pathogenic role in C9orf72-related ALS. The prominent feature of these patients would be increased visual system connectivity with the networks responsible of the functional balance between internal and external attention.

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.

All who wander are not lost: the search for homology during homologous recombination

Homologous recombination (HR) is a template-based DNA double-strand break repair pathway that functions to maintain genomic integrity. A vital component of the HR reaction is the identification of template DNA to be used during repair. This occurs through a mechanism known as the homology search. The homology search occurs in two steps: a collision step in which two pieces of DNA are forced to collide and a selection step that results in homologous pairing between matching DNA sequences. Selection of a homologous template is facilitated by recombinases of the RecA/Rad51 family of proteins in cooperation with helicases, translocases, and topoisomerases that determine the overall fidelity of the match. This menagerie of molecular machines acts to regulate critical intermediates during the homology search. These intermediates include recombinase filaments that probe for short stretches of homology and early strand invasion intermediates in the form of displacement loops (D-loops) that stabilize paired DNA. Here, we will discuss recent advances in understanding how these specific intermediates are regulated on the molecular level during the HR reaction. We will also discuss how the stability of these intermediates influences the ultimate outcomes of the HR reaction. Finally, we will discuss recent physiological models developed to explain how the homology search protects the genome.

Readthrough events in plants reveal plasticity of stop codons

Stop codon readthrough (SCR) has important biological implications but remains largely uncharacterized. Here, we identify 1,009 SCR events in plants using a proteogenomic strategy. Plant SCR candidates tend to have shorter transcript lengths and fewer exons and splice variants than non-SCR transcripts. Mass spectrometry evidence shows that stop codons involved in SCR events can be recoded as 20 standard amino acids, some of which are also supported by suppressor tRNA analysis. We also observe multiple functional signals in 34 maize extended proteins and characterize the structural and subcellular localization changes in the extended protein of basic transcription factor 3. Furthermore, the SCR events exhibit non-conserved signature, and the extensions likely undergo protein-coding selection. Overall, our study not only characterizes that SCR events are commonly present in plants but also identifies the recoding plasticity of stop codons, which provides important insights into the flexibility of genetic decoding.

Functional characterization of NBS-LRR genes reveals an NBS-LRR gene that mediates resistance against Fusarium wilt

BACKGROUND

Most disease resistance (R) genes in plants encode proteins that contain leucine-rich-repeat (LRR) and nucleotide-binding site (NBS) domains, which belong to the NBS-LRR family. The sequenced genomes of Fusarium wilt-susceptible Vernicia fordii and its resistant counterpart, Vernicia montana, offer significant resources for the functional characterization and discovery of novel NBS-LRR genes in tung tree.

RESULTS

Here, we identified 239 NBS-LRR genes across two tung tree genomes: 90 in V. fordii and 149 in V. montana. Five VmNBS-LRR paralogous were predicted in V. montana, and 43 orthologous were detected between V. fordii and V. montana. The orthologous gene pair Vf11G0978-Vm019719 exhibited distinct expression patterns in V. fordii and V. montana: Vf11G0978 showed downregulated expression in V. fordii, while its orthologous gene Vm019719 demonstrated upregulated expression in V. montana, indicating that this pair may be responsible for the resistance to Fusarium wilt in V. montana. Vm019719 from V. montana, activated by VmWRKY64, was shown to confer resistance to Fusarium wilt in V. montana by a virus-induced gene silencing (VIGS) experiment. However, in the susceptible V. fordii, its allelic counterpart, Vf11G0978, exhibited an ineffective defense response, attributed to a deletion in the promoter's W-box element.

CONCLUSIONS

This study provides the first systematic analysis of NBS-LRR genes in the tung tree and identifies a candidate gene that can be utilized for marker-assisted breeding to control Fusarium wilt in V. fordii.

[Advances of proteostasis network and its stability maintenance mechanism]

Protein is fundamental to life, as it generates protein variants. The maintenance of a dynamic equilibrium in these protein variants, known as protein homeostasis, is crucial for cellular function. Various factors, both endogenous and exogenous, can disrupt protein homeostasis during protein synthesis. These factors include translational error, and biological functions mediated by regulatory factors, and more. When cell accumulate proteins with folding errors, it impairs protein homeostasis, leading to the development of related diseases. In response to protein folding errors, multiple monitoring mechanisms are activated to mediate pathways that sustain the dynamic equilibrium. This review highlights the complex relationships within the proteostasis network, which are influenced by a variety of factors. These insights potentially provide new directions for studying diseases caused by protein synthesis errors.