Linking protein structural and functional change to mutation using amino acid networks

Secondary structure analysis of proteins within the same topology group

The native conformation of a protein plays a decisive role in ensuring its functionality. It is established that the spatial structure of proteins may exhibit a greater degree of conservation than the corresponding amino acid sequences. This study aims to clarify structural distinctions between homologous and non-homologous proteins with identical topology. The analysis focuses on secondary structures with special emphasis on their fraction, distribution along the polypeptide chain, and chirality. Three different groups of proteins with identical topology were considered according to the CATH database: a homologous group of Globins, a group of Phycocyanins, which is often considered as a potential relative of globins, and a diverse assembly of other globin-like proteins. Some structural patterns in the distribution of secondary structure have been identified within Globins. A similar profile was observed in Phycocyanins, in contrast to the third group. In addition, a distinguishable structural motif, including structures such as 310-helix and irregular structure, has been found in both Globins and Phycocyanins, which can be proposed as an evolutionary imprint.

Low nucleotide diversity of the Plasmodium falciparum AP2-EXP2 gene among clinical samples from Ghana

BACKGROUND

PfAP2-EXP2 is located within chromosome 6 of Plasmodium falciparum recently identified to be undergoing an extensive selective sweep in West African isolates. The gene encoding this transcription factor, PfAP2-EXP2, is essential and thus likely subject to purifying selection that limits variants in the parasite population despite its genomic location.

METHODS

72 Plasmodium falciparum field samples and 801 clinical sequences from the Pf6 MalariaGEN dataset of Ghanaian origin, were integrated and analysed.

RESULTS

A total of 14 single nucleotide variants of which 5 were missense variants, were identified after quality checks and filtering. Except for one, all identified variants were rare among the clinical samples obtained in this study (Minor allelic frequency < 0.01). Further results revealed a considerably low dN/dS value (0.208) suggesting the presence of purifying selection. Further, all the mutant amino acids were wildtype residues in AP2-EXP2 orthologous proteins-tentatively suggesting a genus-level conservation of amino acid residues. Computational analysis and predictions corroborated these findings.

CONCLUSIONS

Despite the recent extensive selective sweep within chromosome 6 of West African isolates, PfAP2-EXP2 of Ghanaian origin exhibits low nucleotide diversity and very low dN/dS consistent with purifying selection acting to maintain the function of an essential gene. The conservation of AP2-EXP2 is an important factor that makes it a potential drug target.

From adsorption to crystallization of proteins: Evidence for interface-assisted nucleation

Protein crystallization is among the key processes in biomolecular research, but the underlying mechanisms are still elusive. Here, we address the role of inevitable interfaces for the nucleation process. Quartz crystal microbalance with dissipation monitoring (QCM-D) with simultaneously optical microscopy, confocal microscopy, and grazing-incidence small angle X-rays scattering (GISAXS) were employed to investigate the temporal behavior from the initial stage of protein adsorption to crystallization. Here we studied the crystallization of the Human Serum Albumin (HSA), the most abundant blood protein, in the presence of a charged surface and a trivalent salt. We found evidence for interface-assisted nucleation of crystals. The kinetic stages involved are initial adsorption followed by enhanced adsorption after longer times, subsequent nucleation, and finally crystal growth. The results highlight the importance of interfaces for protein phase behavior and in particular for nucleation.

Genetic and mechanistic evaluation of an individual with para-Bombay phenotype associated with a compound heterozygote comprising two novel FUT1 variants

BACKGROUND

As is well documented, the para-Bombay phenotype is typically characterized by the reduction or absence of ABH antigens on red blood cells but the presence of corresponding antigens in saliva. Herein, the underlying molecular mechanism of an individual with para-Bombay AB phenotype combined with two novel variants of the FUT1 gene was investigated.

MATERIALS AND METHODS

ABH antigens and antibodies were detected in the serum of the proband using conventional serological methods. The coding region nucleotides of the ABO, FUT1, and FUT2 genes were directly sequenced by polymerase chain reaction. Moreover, the FUT1 haploid type in the proband was analyzed by TA clone sequencing. The 3D structure of wild-type and mutant fucosyltransferases were simulated and analyzed using Phyre2 and Pymol software. Lastly, the effect of missense substitution on the function of fucosyltransferase was predicted by the Polymorphism Phenotyping algorithm (PolyPhen-2) and MutationTaster.

RESULTS

ABH antigens were noted to be absent on the surface of red blood cells of the proband. The ABO genotype was ABO*A1.02/ABO*B.01, while the FUT2 genotype was FUT2*01/FUT2*c.357T. Interestingly, two novel missense variants (c.289G>A, p.Ala97Thr and c.575G>C, p.Arg192Pro) and one synonymous SNP (c.840G>A) were identified in the FUT1 gene. Furthermore, c.289G>A was detected in one haploid type, whereas c.575G>C and c.840G>A were discovered in another haploid type. Meanwhile, in silico analysis revealed that amino acid substitution caused by missense variants altered the partial spatial structure of the α-helices where residues 97 and 298 were located using 3D homology modeling software. Finally, both missense variants were defined as probably damaging based on PolyPhen-2 prediction.

DISCUSSION

Two novel FUT1 variants were identified in a Chinese individual with para-Bombay AB phenotype, which can expand our understanding of the molecular mechanism underlying the para-Bombay phenotype and contribute to improving the safety of blood transfusion.

The GBA1 K198E Variant Is Associated with Suppression of Glucocerebrosidase Activity, Autophagy Impairment, Oxidative Stress, Mitochondrial Damage, and Apoptosis in Skin Fibroblasts

Parkinson's disease (PD) is a multifactorial, chronic, and progressive neurodegenerative disorder inducing movement alterations as a result of the loss of dopaminergic (DAergic) neurons of the pars compacta in the substantia nigra and protein aggregates of alpha synuclein (α-Syn). Although its etiopathology agent has not yet been clearly established, environmental and genetic factors have been suggested as the major contributors to the disease. Mutations in the glucosidase beta acid 1 (GBA1) gene, which encodes the lysosomal glucosylceramidase (GCase) enzyme, are one of the major genetic risks for PD. We found that the GBA1 K198E fibroblasts but not WT fibroblasts showed reduced catalytic activity of heterozygous mutant GCase by -70% but its expression levels increased by 3.68-fold; increased the acidification of autophagy vacuoles (e.g., autophagosomes, lysosomes, and autolysosomes) by +1600%; augmented the expression of autophagosome protein Beclin-1 (+133%) and LC3-II (+750%), and lysosomal-autophagosome fusion protein LAMP-2 (+107%); increased the accumulation of lysosomes (+400%); decreased the mitochondrial membrane potential (∆Ψm) by -19% but the expression of Parkin protein remained unperturbed; increased the oxidized DJ-1Cys106-SOH by +900%, as evidence of oxidative stress; increased phosphorylated LRRK2 at Ser935 (+1050%) along with phosphorylated α-synuclein (α-Syn) at pathological residue Ser129 (+1200%); increased the executer apoptotic protein caspase 3 (cleaved caspase 3) by +733%. Although exposure of WT fibroblasts to environmental neutoxin rotenone (ROT, 1 μM) exacerbated the autophagy-lysosomal system, oxidative stress, and apoptosis markers, ROT moderately increased those markers in GBA1 K198E fibroblasts. We concluded that the K198E mutation endogenously primes skin fibroblasts toward autophagy dysfunction, OS, and apoptosis. Our findings suggest that the GBA1 K198E fibroblasts are biochemically and molecularly equivalent to the response of WT GBA1 fibroblasts exposed to ROT.

Strategies and procedures to generate chimeric DNA polymerases for improved applications

Chimeric DNA polymerase with notable performance has been generated for wide applications including DNA amplification and molecular diagnostics. This rational design method aims to improve specific enzymatic characteristics or introduce novel functions by fusing amino acid sequences from different proteins with a single DNA polymerase to create a chimeric DNA polymerase. Several strategies prove to be efficient, including swapping homologous domains between polymerases to combine benefits from different species, incorporating additional domains for exonuclease activity or enhanced binding ability to DNA, and integrating functional protein along with specific protein structural pattern to improve thermal stability and tolerance to inhibitors, as many cases in the past decade shown. The conventional protocol to develop a chimeric DNA polymerase with desired traits involves a Design-Build-Test-Learn (DBTL) cycle. This procedure initiates with the selection of a parent polymerase, followed by the identification of relevant domains and devising a strategy for fusion. After recombinant expression and purification of chimeric polymerase, its performance is evaluated. The outcomes of these evaluations are analyzed for further enhancing and optimizing the functionality of the polymerase. This review, centered on microorganisms, briefly outlines typical instances of chimeric DNA polymerases categorized, and presents a general methodology for their creation. KEY POINTS: • Chimeric DNA polymerase is generated by rational design method. • Strategies include domain exchange and addition of proteins, domains, and motifs. • Chimeric DNA polymerase exhibits improved enzymatic properties or novel functions.

Opening SCID newborn screening for novel exon genetic variants through whole-exome sequencing in China

BACKGROUND

Severe combined immunodeficiency (SCID) is the most fatal form of inherited primary immunodeficiency disease. Known molecular defect mutations occur in most children with SCID.

METHODS

Herein, we report Adenosine Deaminase-SCID (ADA-SCID) using whole-exome sequencing (WES), explore exome mutational landscape and significance for 17 SCID samples, and verify the mutated exon genes using the Gene Expression Omnibus (GEO) datasets. A total of 250 patients, who were hospitalized at the Neonatal Intensive Care Unit (NICU) of The Seventh Medical Center of the PLA General Hospital for 3 years (from 2017 to 2020), were screened for SCID. We collected mutated genes from the WES data of 17 SCID children. GSE609 and GSE99176 cohorts were used to identify the expressions of mutated exon genes and molecular features in SCID. Gene set variation analyses (GSVA) and correlation analyses were performed.

RESULTS

The detection rate with approximately 6.8 % (17/250) of SCID is high in the NICU. A total of 16 genes were identified among 17 SCID samples, of which the Top 2 genes (MUC6 and RP11-683L23.1) might be crucial in the progression of SCID with 94 % mutation frequency. Furthermore, CNN2 and SCGB1C1 had significant co-mutations and may cooperate to affect SCID development. Importantly, the phylogenetic tree classification results of 17 SCID samples are more correlated to MUC6 with the most significant mutations. Expression profiles of seven mutated genes and five mutated genes were documented in GSE609 and GSE99176 cohorts based on microarray, respectively. Several immune-related pathways were significantly enriched, and Foxd4, differing from the other four mutated genes, was inversely correlated with the GSVA-enriched pathway.

CONCLUSION

Due to its high detection rate (6.8%) and fatality rate (100%), the inclusion of SCID in newborn screening (NBS) is urgent for children in China. The WES successfully identified several common exonic variants (e.g., MUC6) and depicted the feature of mutations and evolution, which will help develop new diagnostic methods for SCID.

Interaction between polydopamine-based IONPs and human serum albumin (HSA): a spectroscopic analysis with cytotoxicity impact

Iron oxide nanoparticles (IONPs) have been extensively explored in biomedicine, bio-sensing, hyperthermia, and drug/gene delivery, attributed to their versatile and tunable properties. However, owing to its numerous applications, the functionalization of IONPs with appropriate materials is in demand. To achieve optimal functionalization of IONPs, polydopamine (PDA) was utilized due to its ability to provide a superior functionalized surface, near-infrared light absorption, and adhesive nature to customize desired functionalized IONPs. This notion of involving PDA led to the successful synthesis of magnetite-PDA nanoparticles, where PDA is surface-coated on magnetite (Fe3O4@PDA). The Fe3O4@PDA nanoparticles were characterized using techniques like TEM, FESEM, PXRD, XPS, VSM, and FTIR, suggesting PDA's successful attachment with magnetite crystal structure retention. Human serum albumin (HSA), the predominant protein in blood plasma, interacts with the delivered nanoparticles. Therefore, we have employed various spectroscopic techniques, along with cytotoxicity, to inspect the effect of Fe3O4@PDA NPs on the stability and structure of HSA. The structural alterations were examined using circular dichroism (CD) and synchronous fluorescence spectroscopy (SFS). It has been observed that there are no structural perturbations in the secondary structure of the HSA protein after interaction with Fe3O4@PDA. Studies using steady-state fluorescence revealed that the inherent fluorescence intensities of HSA were suppressed after interaction with Fe3O4@PDA. In addition, temperature-dependent fluorescence measurements suggested that the type of quenching consists of both static and dynamic quenching simultaneously. A cytotoxicity study in Drosophila melanogaster larvae revealed no cytotoxic effects but did show a minor genotoxic effect only at higher concentrations.

Genomic characterization and virulence gene profiling of Erysipelothrix rhusiopathiae isolated from widespread muskox mortalities in the Canadian Arctic Archipelago

BACKGROUND

Muskoxen are important ecosystem components and provide food, economic opportunities, and cultural well-being for Indigenous communities in the Canadian Arctic. Between 2010 and 2021, Erysipelothrix rhusiopathiae was isolated from carcasses of muskoxen, caribou, a seal, and an Arctic fox during multiple large scale mortality events in the Canadian Arctic Archipelago. A single strain ('Arctic clone') of E. rhusiopathiae was associated with the mortalities on Banks, Victoria and Prince Patrick Islands, Northwest Territories and Nunavut, Canada (2010-2017). The objectives of this study were to (i) characterize the genomes of E. rhusiopathiae isolates obtained from more recent muskox mortalities in the Canadian Arctic in 2019 and 2021; (ii) identify and compare common virulence traits associated with the core genome and mobile genetic elements (i.e. pathogenicity islands and prophages) among Arctic clone versus other E. rhusiopathiae genomes; and iii) use pan-genome wide association studies (GWAS) to determine unique genetic contents of the Arctic clone that may encode virulence traits and that could be used for diagnostic purposes.

RESULTS

Phylogenetic analyses revealed that the newly sequenced E. rhusiopathiae isolates from Ellesmere Island, Nunavut (2021) also belong to the Arctic clone. Of 17 virulence genes analysed among 28 Arctic clone isolates, four genes - adhesin, rhusiopathiae surface protein-A (rspA), choline binding protein-B (cbpB) and CDP-glycerol glycerophosphotransferase (tagF) - had amino acid sequence variants unique to this clone when compared to 31 other E. rhusiopathiae genomes. These genes encode proteins that facilitate E. rhusiopathiae to attach to the host endothelial cells and form biofilms. GWAS analyses using Scoary found several unique genes to be overrepresented in the Arctic clone.

CONCLUSIONS

The Arctic clone of E. rhusiopathiae was associated with multiple muskox mortalities spanning over a decade and multiple Arctic islands with distances over 1000 km, highlighting the extent of its spatiotemporal spread. This clone possesses unique gene content, as well as amino acid variants in multiple virulence genes that are distinct from the other closely related E. rhusiopathiae isolates. This study establishes an essential foundation on which to investigate whether these differences are correlated with the apparent virulence of this specific clone through in vitro and in vivo studies.

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Rapid evolutionary change in trait correlations of single proteins

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein's ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

Discovery of Red-Shifting Mutations in Firefly Luciferase Using High-Throughput Biochemistry

Photinus pyralis luciferase (FLuc) has proven a valuable tool for bioluminescence imaging, but much of the light emitted from the native enzyme is absorbed by endogenous biomolecules. Thus, luciferases displaying red-shifted emission enable higher resolution during deep-tissue imaging. A robust model of how protein structure determines emission color would greatly aid the engineering of red-shifted mutants, but no consensus has been reached to date. In this work, we applied deep mutational scanning to systematically assess 20 functionally important amino acid positions on FLuc for red-shifting mutations, predicting that an unbiased approach would enable novel contributions to this debate. We report dozens of red-shifting mutations as a result, a large majority of which have not been previously identified. Further characterization revealed that mutations N229T and T352M, in particular, bring about unimodal emission with the majority of photons being >600 nm. The red-shifting mutations identified by this high-throughput approach provide strong biochemical evidence for the multiple-emitter mechanism of color determination and point to the importance of a water network in the enzyme binding pocket for altering the emitter ratio. This work provides a broadly applicable mutational data set tying FLuc structure to emission color that contributes to our mechanistic understanding of emission color determination and should facilitate further engineering of improved probes for deep-tissue imaging.

Quantitative mass spectrometry imaging: therapeutics & biomolecules

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.

Using directed evolution to improve hydrogen production in chimeric hydrogenases from algal species

Algae generate hydrogen from sunlight and water utilizing high-energy electrons generated during photosynthesis. The amount of hydrogen produced in heterologous expression of the wild-type hydrogenase is currently insufficient for industrial applications. One approach to improve hydrogen yields is through directed evolution of the DNA of the native hydrogenase. Here, we created 113 chimeric algal hydrogenase gene variants derived from combining segments of three parent hydrogenases, two from Chlamydomonas reinhardtii (CrHydA1 and CrHydA2) and one from Scenedesmus obliquus (HydA1). To generate chimeras, there were seven segments into which each of the parent hydrogenase genes was divided and recombined in a variety of combinations. The chimeric and parental hydrogenase sequences were cloned for heterologous expression in Escherichia coli, and 40 of the resultant enzymes expressed were assayed for H2 production. Chimeric clones that resulted in equal or greater production obtained with the cloned CrHydA1 parent hydrogenase were those comprised of CrHydA1 sequence in segments #1, 2, 3, and/or 4. These best-performing chimeras all contained one common region, segment #2, the part of the sequence known to contain important amino acids involved in proton transfer or hydrogen cluster coordination. The amino acid sequence distances among all chimeric clones to that of the CrHydA1 parent were determined, and the relationship between sequence distances and experimentally-derived H2 production was evaluated. An additional model determined the correlation between electrostatic potential energy surface area ratios and H2 production. The model yielded several algal mutants with predicted hydrogen productions in a range of two to three times that of the wild-type hydrogenase. The mutant data and the model can now be used to predict which specific mutant sequences may result in even higher hydrogen yields. Overall, results provide more precise details in planning future directed evolution to functionally improve algal hydrogenases.

Study on the Mutation of FⅨ Gene in 31 Patients with Type B Hemophilia

Hemophilia B (HB) is an inherited bleeding disorder caused by defects in the FⅨ gene, leading to severe coagulation dysfunction. This study designed eight pairs of primers covering eight exons of the FⅨ gene and used PCR and DNA sequencing to detect FⅨ gene mutations in 31 HB patients. Sequencing results were compared with normal sequences using Chromas software on Blast to identify mutation sites. Findings revealed the CpG dinucleotide region as a mutation hotspot and the 192nd nucleotide (FⅨ192) as a dinucleotide polymorphism site in the Chinese population. Pathogenic mutations included point mutations, deletions, insertions, and mutations affecting amino acids or splicing sites. For cases with only polymorphic sites, further exon sequencing is needed. This study adds new mutation data to the global HB database, supports research on racial differences in FⅨ gene mutations, and contributes to domestic HB statistics. The results aid in understanding the FⅨ gene's role in coagulation, elucidating HB pathogenesis, and providing a basis for future gene therapy.

Lipid and cholesterols modulate the dynamics of SARS-CoV-2 viral ion channel ORF3a and its pathogenic variants

SARS-CoV-2 accessory protein, ORF3a is a putative ion channel which immensely contributes to viral pathogenicity by modulating host immune responses and virus-host interactions. Relatively high expression of ORF3a in diseased individuals and implication with inflammasome activation, apoptosis and autophagy inhibition, ratifies as an effective target for developing vaccines and therapeutics. Herein, we present the elusive dynamics of ORF3a-dimeric state using all-atoms molecular dynamics (MD) simulations at μ-seconds scale in a heterogeneous lipid-mimetic system in multiple replicates. Additionally, we also explore the effect of non-synonymous pathogenic mutations on ORF3a ion channel activity and viral pathogenicity in different SARS-CoV-2 variants using various structure-based protein stability (ΔΔG) tools and computational saturation mutagenesis. Our study ascertains the role of phosphatidylcholines and cholesterol in modulating the structure of ORF3a, which perturbs the size and flexibility of the polar cavity that allows permeation of large cations. Discrete trend in ion channel pore radius and area per lipid arises the premise that presence of lipids might also affect the overall conformation of ORF3a. MD structural-ensembles, in some replicates rationalize the crucial role of TM2 in maintaining the native structure of ORF3a. We also infer that loss of structural stability primarily grounds for pathogenicity in more than half of the pathogenic variants of ORF3a. Overall, the effect of mutation on alteration of ion permeability of ORF3a, proposed in this study brings mechanistic insights into variant consequences on viral membrane proteins of SARS-CoV-2, which can be utilized for the development of novel therapeutics to treat COVID-19 and other coronavirus diseases.

In Silico Evaluation of the Potential Association of the Pathogenic Mutations of Alpha Synuclein Protein with Induction of Synucleinopathies

Alpha synuclein (α-Syn) is a neuronal protein encoded by the SNCA gene and is involved in the development of Parkinson's disease (PD). The objective of this study was to examine in silico the functional implications of non-synonymous single nucleotide polymorphisms (nsSNPs) in the SNCA gene. We used a range of computational algorithms such as sequence conservation, structural analysis, physicochemical properties, and machine learning. The sequence of the SNCA gene was analyzed, resulting in the mapping of 42,272 SNPs that are classified into different functional categories. A total of 177 nsSNPs were identified within the coding region; there were 20 variants that may influence the α-Syn protein structure and function. This identification was made by employing different analytical tools including SIFT, PolyPhen2, Mut-pred, SNAP2, PANTHER, PhD-SNP, SNP&Go, MUpro, Cosurf, I-Mut, and HOPE. Three mutations, V82A, K80E, and E46K, were selected for further examinations due to their spatial positioning within the α-Syn as determined by PyMol. Results indicated that these mutations may affect the stability and function of α-Syn. Then, a molecular dynamics simulation was conducted for the SNCA wildtype and the four mutant variants (p.A18G, p.V82A, p.K80E, and p.E46K). The simulation examined temperature, pressure, density, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (Rg). The data indicate that the mutations p.V82A, p.K80E, and p.E46K reduce the stability and functionality of α-Syn. These findings highlight the importance of understanding the impact of nsSNPs on α-syn structure and function. Our results required verifications in further protein functional and case-control studies. After being verified these findings can be used in genetic testing for the early diagnosis of PD, the evaluation of the risk factors, and therapeutic approaches.

Morphological and molecular characteristics of Plasmodium juxtanucleare in layer chicken from three districts of Yogyakarta, Indonesia

Background and Aim

Blood parasite infections in poultry, such as Plasmodium, are a serious threat to the poultry industry due to their potential to cause economic losses. To date, there has been inadequate research on the morphological and molecular detection of the different Plasmodium species that infect poultry in Indonesia. Therefore, this study aimed to analyze the morphological and molecular characteristics of Plasmodium spp. and the several predisposing factors for Plasmodium infection in layer chickens from three districts of Yogyakarta, Indonesia.

Materials and Methods

One hundred and five blood samples from layer chickens were collected from 13 farms located in three districts of Yogyakarta (Sleman, Bantul, and Kulon Progo) between September and November 2022. Blood samples were subjected to microscopic and polymerase chain reaction (PCR) analyses. Sequencing was performed using basic local alignment search tools to identify the nucleotide structure of cytochrome b. Phylogenetic analysis of Plasmodium was performed using the MEGA-X software.

Results

Microscopic examination revealed that 17/105 positives (16.19%) were positive for blood parasite infection. Trophozoites, erythrocytic meronts, and microgametocytes of Plasmodium were found in blood samples. Based on the morphological examination, the species found in the samples was close to Plasmodium juxtanucleare. Polymerase chain reaction examination revealed that 21/60 samples were positive for Plasmodium (35%). The Plasmodium species identified from the sequenced samples were proven to be P. juxtanucleare. The P. juxtanucleare from Thailand was closely related to samples (99.64%-100%) with a genetic distance of 0%-1%. In addition, age, population, and cage type were not significantly associated with Plasmodium infection.

Conclusion

Based on microscopic and PCR examinations, the Plasmodium species found in the three districts of Yogyakarta was P. juxtanucleare. The genetic distance between samples from the three districts of Yogyakarta was closely related (0%-1%) to P. juxtanucleare from Thailand and Japan. There was no correlation between Plasmodium infection and age, cage type, or population.

Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry

Deep learning models are seeing increased use as methods to predict mutational effects or allowed mutations in proteins. The models commonly used for these purposes include large language models (LLMs) and 3D Convolutional Neural Networks (CNNs). These two model types have very different architectures and are commonly trained on different representations of proteins. LLMs make use of the transformer architecture and are trained purely on protein sequences whereas 3D CNNs are trained on voxelized representations of local protein structure. While comparable overall prediction accuracies have been reported for both types of models, it is not known to what extent these models make comparable specific predictions and/or generalize protein biochemistry in similar ways. Here, we perform a systematic comparison of two LLMs and two structure-based models (CNNs) and show that the different model types have distinct strengths and weaknesses. The overall prediction accuracies are largely uncorrelated between the sequence- and structure-based models. Overall, the two structure-based models are better at predicting buried aliphatic and hydrophobic residues whereas the two LLMs are better at predicting solvent-exposed polar and charged amino acids. Finally, we find that a combined model that takes the individual model predictions as input can leverage these individual model strengths and results in significantly improved overall prediction accuracy.

Structural studies of protein-nucleic acid complexes: A brief overview of the selected techniques

Protein-nucleic acid complexes are involved in all vital processes, including replication, transcription, translation, regulation of gene expression and cell metabolism. Knowledge of the biological functions and molecular mechanisms beyond the activity of the macromolecular complexes can be determined from their tertiary structures. Undoubtably, performing structural studies of protein-nucleic acid complexes is challenging, mainly because these types of complexes are often unstable. In addition, their individual components may display extremely different surface charges, causing the complexes to precipitate at higher concentrations used in many structural studies. Due to the variety of protein-nucleic acid complexes and their different biophysical properties, no simple and universal guideline exists that helps scientists chose a method to successfully determine the structure of a specific protein-nucleic acid complex. In this review, we provide a summary of the following experimental methods, which can be applied to study the structures of protein-nucleic acid complexes: X-ray and neutron crystallography, nuclear magnetic resonance (NMR) spectroscopy, cryogenic electron microscopy (cryo-EM), atomic force microscopy (AFM), small angle scattering (SAS) methods, circular dichroism (CD) and infrared (IR) spectroscopy. Each method is discussed regarding its historical context, advancements over the past decades and recent years, and weaknesses and strengths. When a single method does not provide satisfactory data on the selected protein-nucleic acid complex, a combination of several methods should be considered as a hybrid approach; thus, specific structural problems can be solved when studying protein-nucleic acid complexes.

Using machine learning to predict the effects and consequences of mutations in proteins

Machine and deep learning approaches can leverage the increasingly available massive datasets of protein sequences, structures, and mutational effects to predict variants with improved fitness. Many different approaches are being developed, but systematic benchmarking studies indicate that even though the specifics of the machine learning algorithms matter, the more important constraint comes from the data availability and quality utilized during training. In cases where little experimental data are available, unsupervised and self-supervised pre-training with generic protein datasets can still perform well after subsequent refinement via hybrid or transfer learning approaches. Overall, recent progress in this field has been staggering, and machine learning approaches will likely play a major role in future breakthroughs in protein biochemistry and engineering.

Biological soft matter: intrinsically disordered proteins in liquid-liquid phase separation and biomolecular condensates

The facts that many proteins with crucial biological functions do not have unique structures and that many biological processes are compartmentalized into the liquid-like biomolecular condensates, which are formed via liquid-liquid phase separation (LLPS) and are not surrounded by the membrane, are revolutionizing the modern biology. These phenomena are interlinked, as the presence of intrinsic disorder represents an important requirement for a protein to undergo LLPS that drives biogenesis of numerous membrane-less organelles (MLOs). Therefore, one can consider these phenomena as crucial constituents of a new IDP-LLPS-MLO field. Furthermore, intrinsically disordered proteins (IDPs), LLPS, and MLOs represent a clear link between molecular and cellular biology and soft matter and condensed soft matter physics. Both IDP and LLPS/MLO fields are undergoing explosive development and generate the ever-increasing mountain of crucial data. These new data provide answers to so many long-standing questions that it is difficult to imagine that in the very recent past, protein scientists and cellular biologists operated without taking these revolutionary concepts into account. The goal of this essay is not to deliver a comprehensive review of the IDP-LLPS-MLO field but to provide a brief and rather subjective outline of some of the recent developments in these exciting fields.

Integrative and Comprehensive Pan-Cancer Analysis of Lymphocyte-Specific Protein Tyrosine Kinase in Human Tumors

Lymphocyte-specific protein tyrosine kinase (LCK) is common in a variety of hematologic malignancies but comparatively less common in solid tumors. This study aimed to explore the potential diagnostic and prognostic value of LCK across tumors through integrative and comprehensive pan-cancer analysis, as well as experimental validation. Multiple databases were used to explore the expression, alteration, prognostic value, association with immune infiltration, and potential functional pathways of LCK in pan-cancers. The results were further validated by western blotting and qPCR of patient samples as well as tumor cell lines. High LCK expression typically represents a better prognosis. Notably, drug sensitivity prediction of LCK identified P-529 as a candidate for drug development. Gene Annotations (GO) and KEGG analyses showed significant enrichment of PD-L1 and the T-cell receptor pathway. The results from patient samples and tumor cell lines confirmed these conclusions in LIHC. In conclusion, LCK is differentially expressed in multiple tumors and normal tissues. Further analysis highlighted its association with prognostic implications, pan-cancer genetic alterations, and immune signatures. Our data provide evidence for a diagnostic marker of LCK and the possible use of LCK as a target for the treatment of tumors.

Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations

The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individual mutations have been shown to contribute to viral replication and fitness, suggesting a possible role of other unexplored mutations in viral evolution. We observed that the mutations 241C>T in the 5' untranslated region (UTR), 3037C>T in nsp3, 14408C>T in the RNA-dependent RNA polymerase (RdRp), and 23403A>G in spike are correlated with each other and were grouped in a single cluster by hierarchical clustering. These mutations have replaced the wild-type nucleotides in SARS-CoV-2 sequences. Additionally, we employed a suite of computational tools to investigate the effects of T85I (1059C>T), P323L (14408C>T), and Q57H (25563G>T) mutations in nsp2, RdRp, and the ORF3a protein of SARS-CoV-2, respectively. We observed that the mutations T85I and Q57H tend to be deleterious and destabilize the respective wild-type protein, whereas P323L in RdRp tends to be neutral and has a stabilizing effect. IMPORTANCE We performed a meta-analysis on SARS-CoV-2 genomes categorized by collection month and identified several significant mutations. Pearson correlation analysis of these significant mutations identified 16 comutations having absolute correlation coefficients of >0.4 and a frequency of >30% in the genomes used in this study. The correlation results were further validated by another statistical tool called hierarchical clustering, where mutations were grouped in clusters on the basis of their similarity. We identified several positive and negative correlations among comutations in SARS-CoV-2 isolates from around the world which might contribute to viral pathogenesis. The negative correlations among some of the mutations in SARS-CoV-2 identified in this study warrant further investigations. Further analysis of mutations such as T85I in nsp2 and Q57H in ORF3a protein revealed that these mutations tend to destabilize the protein relative to the wild type, whereas P323L in RdRp is neutral and has a stabilizing effect. Thus, we have identified several comutations which can be further characterized to gain insights into SARS-CoV-2 evolution.

Paleoproteomics

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.