Identification Of Proteins Research Articles

Identification of odorant binding protein and chemosensory protein genes in Protegira songi (Lepidoptera Noctuidae) via transcriptome analysis

The larvae of Protegira songi Chen & Zhang are notorious defoliator specifically infesting the medicinal plant Eucommia ulmoides Oliver. In insects, Odorant binding proteins (OBPs) and chemosensory proteins (CSPs) are highly expressed in olfactory organs and play essential roles in perceiving female pheromone and host volatiles by binding and transporting odorant compounds. In this study, 17 OBPs and 16 CSPs were identified from P. songi by transcriptome analysis. Sequence alignment indicated that PsonOBPs and PsonCSPs share no identity with each other in protein sequence. The overall structures of PsonOBPs and PsonCSPs are mainly constructed by α-helix bundles and loops. But the distribution of conserved cysteine residues and arrangement of α-helix are varied between PsonOBPs and PsonCSPs. Putative ligand binding cavities were found in these predicted protein structures. Expression profiles of PsonOBPs and PsonCSPs in adults and larvae were determined by RT-PCR which showed that 16 PsonOBPs and 11 PsonCSPs were expressed in adult antennae or/and larval head. PsonGOBPs, PsonPBPs, PsonOBP5, PsonOBP7, and PsonCSP6 were preferentially expressed in olfactory associated tissues. Our results suggest that the PsonOBPs and PsonCSPs that contain ligand cavity and are highly enriched in olfactory tissues may play roles in chemosensory perception of P. songi, and the transcriptome data may facilitate the studies on the olfactory mechanism of P. songi specifically choosing E. ulmoides as host.

ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins.

Prokaryotic DNA binding proteins (DBPs) play pivotal roles in governing gene regulation, DNA replication, and various cellular functions. Accurate computational models for predicting prokaryotic DBPs hold immense promise in accelerating the discovery of novel proteins, fostering a deeper understanding of prokaryotic biology, and facilitating the development of therapeutics targeting for potential disease interventions. However, existing generic prediction models often exhibit lower accuracy in predicting prokaryotic DBPs. To address this gap, we introduce ProkDBP, a novel machine learning-driven computational model for prediction of prokaryotic DBPs. For prediction, a total of nine shallow learning algorithms and five deep learning models were utilized, with the shallow learning models demonstrating higher performance metrics compared to their deep learning counterparts. The light gradient boosting machine (LGBM), coupled with evolutionarily significant features selected via random forest variable importance measure (RF-VIM) yielded the highest five-fold cross-validation accuracy. The model achieved the highest auROC (0.9534) and auPRC (0.9575) among the 14 machine learning models evaluated. Additionally, ProkDBP demonstrated substantial performance with an independent dataset, exhibiting higher values of auROC (0.9332) and auPRC (0.9371). Notably, when benchmarked against several cutting-edge existing models, ProkDBP showcased superior predictive accuracy. Furthermore, to promote accessibility and usability, ProkDBP (https://iasri-sg.icar.gov.in/prokdbp/) is available as an online prediction tool, enabling free access to interested users. This tool stands as a significant contribution, enhancing the repertoire of resources for accurate and efficient prediction of prokaryotic DBPs.

Comparative proteomic analysis of dental pulp from supernumerary and normal permanent teeth

ObjectivesTo obtain and compare the protein profiles of supernumerary and normal permanent dental pulp tissues.Materials and methodsDental pulp tissues were obtained from supernumerary and normal permanent teeth. Proteins were extracted and analyzed by liquid chromatography-tandem mass spectrometry (LC/MS-MS). Protein identification and quantification from MS data was performed with MaxQuant. Statistical analysis was conducted using Metaboanalyst to identify differentially expressed proteins (DEPs) (P-value < 0.05, fold-change > 2). Gene Ontology enrichment analyses were performed with gProfiler.ResultsA total of 3,534 proteins were found in normal dental pulp tissue and 1,093 in supernumerary dental pulp tissue, with 174 DEPs between the two groups. This analysis revealed similar functional characteristics in terms of cellular component organization, cell differentiation, developmental process, and response to stimulus, alongside exclusive functions unique to normal permanent dental pulp tissues such as healing, vascular development and cell death. Upon examination of DEPs, these proteins were associated with the processes of wound healing and apoptosis.ConclusionsThis study provides a comprehensive understanding of the protein profile of dental pulp tissue, including the first such profiling of supernumerary permanent dental pulp. There are functional differences between the proteomic profiles of supernumerary and normal permanent dental pulp tissue, despite certain biological similarities between the two groups. Differences in protein expression were identified, and the identified DEPs were linked to the healing and apoptosis processes.Clinical relevanceThis discovery enhances our knowledge of supernumerary and normal permanent pulp tissue, and serves as a valuable reference for future studies on supernumerary teeth.

Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP.

Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.

Integrated proteomic, phosphoproteomic, and N-glycoproteomic analyses of small extracellular vesicles from C2C12 myoblasts identify specific PTM patterns in ligand-receptor interactions

Small extracellular vesicles (sEVs) are important mediators of intercellular communication by transferring of functional components (proteins, RNAs, and lipids) to recipient cells. Some PTMs, including phosphorylation and N-glycosylation, have been reported to play important role in EV biology, such as biogenesis, protein sorting and uptake of sEVs. MS-based proteomic technology has been applied to identify proteins and PTM modifications in sEVs. Previous proteomic studies of sEVs from C2C12 myoblasts, an important skeletal muscle cell line, focused on identification of proteins, but no PTM information on sEVs proteins is available.In this study, we systematically analyzed the proteome, phosphoproteome, and N-glycoproteome of sEVs from C2C12 myoblasts with LC–MS/MS. In-depth analyses of the three proteomic datasets revealed that the three proteomes identified different catalogues of proteins, and PTMomic analysis could expand the identification of cargos in sEVs. At the proteomic level, a high percentage of membrane proteins, especially tetraspanins, was identified. The sEVs-derived phosphoproteome had a remarkably high level of tyrosine-phosphorylated sites. The tyrosine-phosphorylated proteins might be involved with EPH-Ephrin signaling pathway. At the level of N-glycoproteomics, several glycoforms, such as complex N-linked glycans and sialic acids on glycans, were enriched in sEVs. Retrieving of the ligand-receptor interaction in sEVs revealed that extracellular matrix (ECM) and cell adhesion molecule (CAM) represented the most abundant ligand-receptor pairs in sEVs. Mapping the PTM information on the ligands and receptors revealed that N-glycosylation mainly occurred on ECM and CAM proteins, while phosphorylation occurred on different categories of receptors and ligands. A comprehensive PTM map of ECM-receptor interaction and their components is also provided.In summary, we conducted a comprehensive proteomic and PTMomic analysis of sEVs of C2C12 myoblasts. Integrated proteomic, phosphoproteomic, and N-glycoproteomic analysis of sEVs might provide some insights about their specific uptake mechanism.

MACSPI enables tissue-selective proteomic and interactomic analyses in multicellular organisms

Multicellular organisms are composed of many tissue types that have distinct morphologies and functions, which are largely driven by specialized proteomes and interactomes. To define the proteome and interactome of a specific type of tissue in an intact animal, we developed a localized proteomics approach called Methionine Analog-based Cell-Specific Proteomics and Interactomics (MACSPI). This method uses the tissue-specific expression of an engineered methionyl-tRNA synthetase to label proteins with a bifunctional amino acid 2-amino-5-diazirinylnonynoic acid in selected cells. We applied MACSPI in Caenorhabditis elegans, a model multicellular organism, to selectively label, capture, and profile the proteomes of the body wall muscle and the nervous system, which led to the identification of tissue-specific proteins. Using the photo-cross-linker, we successfully profiled HSP90 interactors in muscles and neurons and identified tissue-specific interactors and stress-related interactors. Our study demonstrates that MACSPI can be used to profile tissue-specific proteomes and interactomes in intact multicellular organisms.

Identification of cellular retinoic acid binding protein 2 (CRABP2) as downstream target of nuclear factor 1/X (NFIX): implications for skeletal dysplasia syndromes

Abstract Nuclear factor I/X (NFIX) mutations are associated with two skeletal dysplasias, Marshall-Smith (MSS) and Malan (MAL) syndromes. NFIX encodes a transcription factor that regulates expression of genes, including Bobby sox (BBX) and glial fibrillary acidic protein (GFAP) in neural progenitor cells and astrocytes, respectively. To elucidate the role of NFIX mutations in MSS, we studied their effects in fibroblast cell lines obtained from 5 MSS unrelated patients and 3 unaffected individuals. The 5 MSS NFIX frameshift mutations in exons 6-8 comprised 3 deletions (c.819-732_1079-948del, c. 819-471_1079-687del, c.819-592_1079-808del), an insertion (c. 1037_1038insT) and a duplication (c.1090dupG). Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot analyses using MSS and unrelated control fibroblasts and in vitro expression studies in monkey kidney fibroblast (COS-7) cells showed that frameshift mutations in NFIX exons 6-8 generated mutant transcripts that were not cleared by nonsense-mediated-decay mechanisms and encoded truncated NFIX proteins. Moreover, BBX or GFAP expression were unaffected in the majority of MSS fibroblasts. To identify novel NFIX downstream target genes, RNA sequencing and proteomics analyses were performed on mouse embryonic fibroblast (MEF) cells derived from control Nfix+/+, Nfix+/Del2, Nfix+/Del24, NfixDel24/Del24, Nfix+/Del140 and NfixDel140/Del140 mice, compared to NfixDel2/Del2 mice which had developmental, skeletal and neural abnormalities. This identified 191 transcripts and 815 proteins misregulated in NfixDel2/Del2 MEFs with ≥2-fold-change (p &amp;lt; 0.05). Validation studies using qRT-PCR and Western blot analyses confirmed that two genes, cellular retinoic acid binding protein 2 (Crabp2) and vascular cell adhesion molecule 1 (Vcam1), were misregulated at the RNA and protein levels in NfixDel2/Del2 MEFs, and that CRABP2 and VCAM1 expression were altered in 60-100% of MSS fibroblast cells. Furthermore, in vitro luciferase reporter assays confirmed that NFIX directly regulates CRABP2 promoter activity. Thus, these altered genes and pathways may represent possible targets for drugs as potential treatments and therapies for MSS.

TurboID mapping reveals the exportome of secreted intrinsically disordered proteins in the transforming parasite Theileria annulata.

Theileria annulata is a tick-transmitted apicomplexan parasite that gained the unique ability among parasitic eukaryotes to transform its host cell, inducing a fatal cancer-like disease in cattle. Understanding the mechanistic interplay between the host cell and malignant Theileria species that drives this transformation requires the identification of responsible parasite effector proteins. In this study, we used TurboID-based proximity labeling, which unbiasedly identified secreted parasite proteins within host cell compartments. By fusing TurboID to nuclear export or localization signals, we biotinylated proteins in the vicinity of the ligase enzyme in the nucleus or cytoplasm of infected macrophages, followed by mass spectrometry analysis. Our approach revealed with high confidence nine nuclear and four cytosolic candidate parasite proteins within the host cell compartments, eight of which had no orthologs in non-transforming T. orientalis. Strikingly, all eight of these proteins are predicted to be highly intrinsically disordered proteins. We discovered a novel tandem arrayed protein family, nuclear intrinsically disordered proteins (NIDP) 1-4, featuring diverse functions predicted by conserved protein domains. Particularly, NIDP2 exhibited a biphasic host cell-cycle-dependent localization, interacting with the EB1/CD2AP/CLASP1 parasite membrane complex at the schizont surface and the tumor suppressor stromal antigen 2 (STAG2), a cohesion complex subunit, in the host nucleus. In addition to STAG2, numerous NIDP2-associated host nuclear proteins implicated in various cancers were identified, shedding light on the potential role of the T. annulata exported protein family NIDP in host cell transformation and cancer-related pathways.IMPORTANCETurboID proximity labeling was used to identify secreted proteins of Theileria annulata, an apicomplexan parasite responsible for a fatal, proliferative disorder in cattle that represents a significant socio-economic burden in North Africa, central Asia, and India. Our investigation has provided important insights into the unique host-parasite interaction, revealing secreted parasite proteins characterized by intrinsically disordered protein structures. Remarkably, these proteins are conspicuously absent in non-transforming Theileria species, strongly suggesting their central role in the transformative processes within host cells. Our study identified a novel tandem arrayed protein family, with nuclear intrinsically disordered protein 2 emerging as a central player interacting with established tumor genes. Significantly, this work represents the first unbiased screening for exported proteins in Theileria and contributes essential insights into the molecular intricacies behind the malignant transformation of immune cells.

Proteomic Identification of Plasma Proteins Associated with Future Dementia Development.

Proteomic Identification of Plasma Proteins Associated with Future Dementia Development.

Understanding bacterial pathogen diversity: A proteogenomic analysis and use of an array of genome assemblies to identify novel virulence factors of the honey bee bacterial pathogen Paenibacillus larvae.

Mass spectrometry proteomics data are typically evaluated against publicly available annotated sequences, but the proteogenomics approach is a useful alternative. A single genome is commonly utilized in custom proteomic and proteogenomic data analysis. We pose the question of whether utilizing numerous different genome assemblies in a search database would be beneficial. We reanalyzed raw data from the exoprotein fraction of four reference Enterobacterial Repetitive Intergenic Consensus (ERIC) I-IV genotypes of the honey bee bacterial pathogen Paenibacillus larvae and evaluated them against three reference databases (from NCBI-protein, RefSeq, and UniProt) together with an array of protein sequences generated by six-frame direct translation of 15 genome assemblies from GenBank. The wide search yielded 453 protein hits/groups, which UpSet analysis categorized into 50 groups based on the success of protein identification by the 18 database components. Nine hits that were not identified by a unique peptide were not considered for marker selection, which discarded the only protein that was not identified by the reference databases. We propose that the variability in successful identifications between genome assemblies is useful for marker mining. The results suggest that various strains of P. larvae can exhibit specific traits that set them apart from the established genotypes ERIC I-V.

Iron-sulfur protein odyssey: exploring their cluster functional versatility and challenging identification.

Iron-sulfur (Fe-S) clusters are an essential and ubiquitous class of protein-bound prosthetic centers that are involved in a broad range of biological processes (e.g. respiration, photosynthesis, DNA replication and repair and gene regulation) performing a wide range of functions including electron transfer, enzyme catalysis, and sensing. In a general manner, Fe-S clusters can gain or lose electrons through redox reactions, and are highly sensitive to oxidation, notably by small molecules such as oxygen and nitric oxide. The [2Fe-2S] and [4Fe-4S] clusters, the most common Fe-S cofactors, are typically coordinated by four amino acid side chains from the protein, usually cysteine thiolates, but other residues (e.g. histidine, aspartic acid) can be found. While diversity in cluster coordination ensures the functional variety of the Fe-S clusters, the lack of conserved motifs makes new Fe-S protein identification challenging especially when the Fe-S cluster is also shared between two proteins as observed in several dimeric transcriptional regulators and in the mitoribosome. Thanks to the recent development of in cellulo, in vitro and in silico approaches, new Fe-S proteins are still regularly identified, highlighting the functional diversity of this class of proteins. In this review, we will present three main functions of the Fe-S clusters and explain the difficulties encountered to identify Fe-S proteins and methods that have been employed to overcome these issues.

Identification and Quantification of Human Relaxin Proteins by Immunoaffinity-Mass Spectrometry.

The human relaxins belong to the Insulin/IGF/Relaxin superfamily of peptide hormones, and their physiological function is primarily associated with reproduction. In this study, we focused on a prostate tissue-specific relaxin RLN1 (REL1_HUMAN protein) and a broader tissue specificity RLN2 (REL2_HUMAN protein). Due to their structural similarity, REL1 and REL2 proteins were collectively named a 'human relaxin protein' in previous studies and were exclusively measured by immunoassays. We hypothesized that the highly selective and sensitive immunoaffinity-selected reaction monitoring (IA-SRM) assays would reveal the identity and abundance of the endogenous REL1 and REL2 in biological samples and facilitate the evaluation of these proteins for diagnostic applications. High levels of RLN1 and RLN2 transcripts were found in prostate and breast cancer cell lines by RT-PCR. However, no endogenous prorelaxin-1 or mature REL1 were detected by IA-SRM in cell lines, seminal plasma, or blood serum. The IA-SRM assay of REL2 demonstrated its undetectable levels (<9.4 pg/mL) in healthy control female and male sera and relatively high levels of REL2 in maternal sera across different gestational weeks (median 331 pg/mL; N = 120). IA-SRM assays uncovered potential cross-reactivity and nonspecific binding for relaxin immunoassays. The developed IA-SRM assays will facilitate the investigation of the physiological and pathological roles of REL1 and REL2 proteins.

Ion Moblity Mass Spectrometry in Multi-omics Studies

Mass spectrometry (MS) as an analytical technique enables the identification and quantitative determination of proteins, metabolites, or lipids in a studied sample. However, this method has limitations regarding the number of molecules that can be identified at a given time. To increase the number of identifications, the application of ion mobility spectrometry (IMS) can be employed. This technique allows the separation of ions based on their mobility while traversing the analyser in a gradient of an electromagnetic field and opposing gas pressure. The separation is performed in conjunction with MS analysis, adding another dimension to the analysis, resulting in a significant improvement in the number of identified compounds and a reduction in noise. Alternatively, while maintaining the same number of identifications, analysis can be performed in a shorter time period. It is crucial to pay special attention to the type of IMS analyser used, as its specific implementation dictates further stages of analysis and ion detection capabilities.

Super-resolution proximity labeling with enhanced direct identification of biotinylation sites

Promiscuous labeling enzymes, such as APEX2 or TurboID, are commonly used in in situ biotinylation studies of subcellular proteomes or protein–protein interactions. Although the conventional approach of enriching biotinylated proteins is widely implemented, in-depth identification of specific biotinylation sites remains challenging, and current approaches are technically demanding with low yields. A novel method to systematically identify specific biotinylation sites for LC-MS analysis followed by proximity labeling showed excellent performance compared with that of related approaches in terms of identification depth with high enrichment power. The systematic identification of biotinylation sites enabled a simpler and more efficient experimental design to identify subcellular localized proteins within membranous organelles. Applying this method to the processing body (PB), a non-membranous organelle, successfully allowed unbiased identification of PB core proteins, including novel candidates. We anticipate that our newly developed method will replace the conventional method for identifying biotinylated proteins labeled by promiscuous labeling enzymes.

SLC34A2 promotes cell proliferation by activating STX17-mediated autophagy in esophageal squamous cell carcinoma.

Solute carrier family 34 member 2 (SLC34A2) has been implicated in the development of various malignancies. However, the clinical significance and underlying molecular mechanisms of SLC34A2 in esophageal squamous cell carcinoma (ESCC) remain elusive. Western blotting, quantitative real-time PCR and immunohistochemistry were utilized to evaluate the expression levels of SLC34A2 mRNA/protein in ESCC cell lines or tissues. Kaplan-Meier curves were employed for survival analysis. CCK-8, colony formation, EdU and xenograft tumor model assays were conducted to determine the impact of SLC34A2 on ESCC cell proliferation. Cell cycle was examined using flow cytometry. RNA-sequencing and enrichment analysis were carried out to explore the potential signaling pathways. The autophagic flux was evaluated by western blotting, mRFP-GFP-LC3 reporter system and transmission electron microscopy. Immunoprecipitation and mass spectrometry were utilized for identification of potential SLC34A2-interacting proteins. Cycloheximide (CHX) chase and ubiquitination assays were conducted to test the protein stability. The expression of SLC34A2 was significantly upregulated in ESCC and correlated with unfavorable clinicopathologic characteristics particularly the Ki-67 labeling index and poor prognosis of ESCC patients. Overexpression of SLC34A2 promoted ESCC cell proliferation, while silencing SLC34A2 had the opposite effect. Moreover, SLC34A2 induced autophagy to promote ESCC cell proliferation, whereas inhibition of autophagy suppressed the proliferation of ESCC cells. Further studies showed that SLC34A2 interacted with an autophagy-related protein STX17 to promote autophagy and proliferation of ESCC cells by inhibiting the ubiquitination and degradation of STX17. These findings indicate that SLC34A2 may serve as a prognostic biomarker for ESCC.

Milk Fat Globule Proteins Are Relevant Bovine Milk Allergens in Patients with α‐Gal Syndrome

Alpha-gal syndrome (AGS) is a mammalian meat allergy associated with tick bites and specific IgE to the oligosaccharide galactose-α-1,3-galactose (α-gal). Recent studies have shown that 10-20% of AGS patients also react to the dairy proteins. Considering the already described role of the meat lipid fraction in AGS manifestations, the aim of this work has been to investigate whether the milk fat globule proteins (MFGPs) could be involved in AGS. The MFGPs are extracted and their recognition by the IgE of AGS patients is proved through immunoblotting experiments. The identification of the immunoreactive proteins by LC-HRMS analysis allows to demonstrate for the first time that butyrophillin, lactadherin, and xanthine oxidase (XO) are α-gal glycosylated. The role of xanthine oxidase seems to be prevalent since it is highly recognized byboth the anti-α-gal antibody and AGS patient sera. The results obtained in this study provide novel insights in the characterization of α-Gal carrying glycoproteins in bovine milk, supporting the possibility that milk, especially in its whole form, may give reactions in AGS patients. Although additional factors are probably associated with the clinical manifestations, the avoidance of milk and milk products should be considered in individuals with AGS showing symptoms related to milk consumption.

Characterization of effective, simple, and low-cost precipitation methods for depleting abundant plasma proteins to enhance the depth and breadth of plasma proteomics.

Plasma is an abundant source of proteins and potential biomarkers to aid in the detection, diagnosis, and prognosis of human diseases. These proteins are often present at low levels in the blood and difficult to identify and measure due to the large dynamic range of proteins. The goal of this work was to characterize and compare various protein precipitation methods related to how they affect the depth and breadth of plasma proteomic studies. Abundant protein precipitation with perchloric acid (PerCA) can increase protein identifications and depth of plasma proteomic studies. Three acid- and four solvent-based precipitation methods were evaluated. All methods tested provided excellent plasma proteomic coverage (>600 identified protein groups) and detected protein in the low pg/mL range. Functional enrichment analysis revealed subtle differences within and larger changes between the precipitant groups. Methanol-based precipitation outperformed the other methods based on identifications and reproducibility. The methods' performance was verified using eight lung cancer patient samples, where >700 protein groups were measured and proteins with an estimated plasma concentration of ∼10pg/mL were detected. Various protein precipitation agents are amenable to extending the depth and breadth of plasma proteomes. These data can guide investigators to implement inexpensive, high-throughput methods for their plasma proteomic workflows.

Recent Progress in the Application of Tau Protein Biosensors for Diagnosis of Neurodegenerative Diseases.

The microtubule-associated Tau protein is found in the central nervous system (CNS) in six major isoforms. Neurodegenerative diseases have been linked to post-translational changes of Tau, most notably phosphorylation. Tau protein's molecular diversity is highly helpful in the identification of neurodegenerative illnesses. Nonetheless, one major obstacle to the early detection of brain illness is the nanoscale identification of tau proteins. The standard methods for identifying tau protein include western blotting, polymerase chain reaction (PCR), and real-time PCR. Enzyme-linked immunosorbent assay (ELISA) is another approach used. The limited sensitivity and specificity of these detections, together with the need for sophisticated equipment, are some of their drawbacks. The development of innovative and complex methods for tau protein screening is necessary to address the aforementioned issues. Biosensors are a cutting-edge instrument that may help identify various neurodegenerative biomarkers as early as feasible. This paper provides an overview of the most recent developments in the detection of neurodegenerative diseases employing biosensors built on nanotechnology and methods for imaging, electrochemical, and optical detection of the Tau protein. Furthermore, we outline the present difficulties and suggest a possible course for biosensor-based detection and intervention in the future.

Identification and Characterization of a Bacterial Periplasmic Solute Binding Protein That Binds l-Amino Acid Amides.

Periplasmic solute-binding proteins (SBPs) are key ligand recognition components of bacterial ATP-binding cassette (ABC) transporters that allow bacteria to import nutrients and metabolic precursors from the environment. Periplasmic SBPs comprise a large and diverse family of proteins, of which only a small number have been empirically characterized. In this work, we identify a set of 610 unique uncharacterized proteins within the SBP_bac_5 family that are found in conserved operons comprising genes encoding (i) ABC transport systems and (ii) putative amidases from the FmdA_AmdA family. From these uncharacterized SBP_bac_5 proteins, we characterize a representative periplasmic SBP from Mesorhizobium sp. A09 (MeAmi_SBP) and show that MeAmi_SBP binds l-amino acid amides but not the corresponding l-amino acids. An X-ray crystal structure of MeAmi_SBP bound to l-serinamide highlights the residues that impart distinct specificity for l-amino acid amides and reveals a structural Ca2+ binding site within one of the lobes of the protein. We show that the residues involved in ligand and Ca2+ binding are conserved among the 610 SBPs from experimentally uncharacterized FmdA_AmdA amidase-associated ABC transporter systems, suggesting these homologous systems are also likely to be involved in the sensing, uptake, and metabolism of l-amino acid amides across many Gram-negative nitrogen-fixing soil bacteria. We propose that MeAmi_SBP is involved in the uptake of such solutes to supplement pathways such as the citric acid cycle and the glutamine synthetase-glutamate synthase pathway. This work expands our currently limited understanding of microbial interactions with l-amino acid amides and bacterial nitrogen utilization.

Regulatory sequence-based discovery of anti-defense genes in archaeal viruses

In silico identification of viral anti-CRISPR proteins (Acrs) has relied largely on the guilt-by-association method using known Acrs or anti-CRISPR associated proteins (Acas) as the bait. However, the low number and limited spread of the characterized archaeal Acrs and Aca hinders our ability to identify Acrs using guilt-by-association. Here, based on the observation that the few characterized archaeal Acrs and Aca are transcribed immediately post viral infection, we hypothesize that these genes, and many other unidentified anti-defense genes (ADG), are under the control of conserved regulatory sequences including a strong promoter, which can be used to predict anti-defense genes in archaeal viruses. Using this consensus sequence based method, we identify 354 potential ADGs in 57 archaeal viruses and 6 metagenome-assembled genomes. Experimental validation identified a CRISPR subtype I-A inhibitor and the first virally encoded inhibitor of an archaeal toxin-antitoxin based immune system. We also identify regulatory proteins potentially akin to Acas that can facilitate further identification of ADGs combined with the guilt-by-association approach. These results demonstrate the potential of regulatory sequence analysis for extensive identification of ADGs in viruses of archaea and bacteria.