Proteomic Fingerprint Research Articles

Assessing the Influence of Selected Permeabilization Methods on Lymphocyte Single-Cell Multi-Omics.

(1) Background: Single-cell multi-omics is a powerful method for the dissection and detection of complicated immunologic functions and synapses. However, most currently available technologies merge datasets of different omics from separate portions of the same sample to generate combined multi-omics. This process is a source of bias, mainly in the field of immunology on cells originating from pluripotent hematopoietic stem cells with high flexibility during maturation. (2) Methods: Although new multi-omics approaches have been developed to use the advantages of cellular and molecular barcoding and next-generation sequencing to solve this issue, one of the main current challenges is intracellular proteomics, which should be combined with other omics data with high importance for immune system studies. We designed this study to evaluate previously recommended minimal permeabilization and fixation methods on the quality and quantity of transcriptomics and proteomics data generated by the BD Rhapsody™ Single-Cell Analysis System. (3) Results: Our findings showed that high-throughput sequencing with advanced quality and read-out is required for the combination of multi-omics outcomes from a permeabilized single cell. Therefore, the HiseqX platform was selected for further analysis. The effect of immune stimulation was observed clearly as the separated clusters of helper and cytotoxic T cells using unsupervised clustering. Importantly, fixation and permeabilization did not affect the general expression profile of unstimulated cells. However, fixation and permeabilization were proved to negatively impact the detection of the whole transcriptome for single-cell assay. Nevertheless, about 60% of the transcriptomic signature of the stimulation was detected. If the measurement of combined surface and intracellular markers is required to be achieved, the modified fixation and permeabilization method is recommended because of a lower transcriptomic loss and more precise proteomic fingerprint detected. (4) Conclusions: The findings of this study support the potential possibility for integrating intracellular proteomics, which needs to be optimized and tested with newly designed oligonucleotide-tagged antibodies targeting intracellular proteins.

Evaluation of MALDI-TOF for identification of Vibrio cholerae and Vibrio parahaemolyticus from growth on agar media

Two methods were compared for their ability to accurately identify Vibrio species of interest: whole genome sequencing as the reference method and MALDI-TOF MS (matrix-assisted laser desorption/ionization-time of flight mass spectrometry) proteome fingerprinting. The accuracy of mass spectrometry–based identification method was evaluated for its ability to accurately identify isolates of Vibrio cholerae and Vibrio parahaemolyticus. Identification result of each isolate obtained by mass spectrometry was compared to identification by whole genome sequencing (WGS). The MALDI-TOF MS system had excellent performance for identification of V. cholerae and V. parahaemolyticus isolates grown on a non-selective solid agar media. Unlike the biochemical characterization performed by API20E. In this study, 161 isolates (V. cholerae, n = 33; V. parahaemolyticus, n = 102; V. spp., n = 23; other enteropathogens, Salmonella and E. coli, n = 3) were used to assess accuracy. The MALDI-TOF MS system was able to accurately identify 100% (33/33) of the V. cholerae isolates and 99.9% (101/102) of V. parahaemolyticus isolates, with 100% for both sensitivity and specificity for V. cholerae and 99% sensitivity and 98% specificity for V. parahaemolyticus. Thus, mass spectrometry for bacterial identification is comparable to the WGS. Furthermore, in comparison to a biochemical characterization, the use of MALDI-TOF MS system shortens the analysis time from over 72 h to less than 24 h.Key points• V. cholerae and V. parahaemolyticus were successfully ID-ed by MALDI-TOF• MALDI-TOF sensitivity and specificity parallels the WGS method of identification• MALDI-TOF is several days faster than the battery of culture-dependent methods

Cytoskeleton Remodeling-Related Proteins Represent a Specific Salivary Signature in PSC Patients.

Primary sclerosing cholangitis (PSC) and Primary biliary cholangitis (PBC) are chronic inflammatory biliary diseases characterized by progressive damage of the bile ducts, resulting in hepatobiliary fibrosis and cirrhosis. Currently, specific biomarkers that allow to distinguish between PSC and PBC do not exist. In this study, we examined the salivary proteome by carrying out a comprehensive and non-invasive screening aimed at highlighting possible quali-quantitative protein deregulations that could be the starting point for the identification of effective biomarkers in future. Saliva samples collected from 6 PBC patients were analyzed using a liquid chromatography-tandem mass spectrometry technique, and the results were compared with those previously obtained in the PSC group. We identified 40 proteins as significantly deregulated in PSC patients compared to the PBC group. The Gene Ontology and pathway analyses highlighted that several proteins (e.g., small integral membrane protein 22, cofilin-1, macrophage-capping protein, plastin-2, and biliverdin reductase A) were linked to innate immune responses and actin cytoskeleton remodeling, which is a critical event in liver fibrosis and cancer progression. These findings provide new foundations for a deeper understanding of the pathophysiology of PSC and demonstrate that saliva is a suitable biological sample for obtaining proteomic fingerprints useful in the search for biomarkers capable of discriminating between the two cholestatic diseases.

New insights into the pathophysiology of rheumatic valve disease based on different genetic and proteomics profiles

Abstract Introduction Rheumatic heart disease (RHD) pathogenesis is not fully understood. Purpose The protein profile in rheumatic heart disease may have a different fingerprint in the aortic and mitral valves, which results in different evolution in terms of valve damage. Methods To evaluate the genetic profile in symptomatic RHD, 4 simultaneous mitral and aortic valves were obtained during valve replacement, as well as 4 "normal" valves from cadavers (Control Group). The expression of 90 genes was evaluated using a customized RT-PCR array kit. A second experiment was carried out to evaluate proteomics. Then, 7 mitral and aortic valves, from the same patient, were also collected during valve surgery. The Control Group consisted of 6 mitral and aortic valves obtained from explanted hearts during heart transplantation due to non-valvular pathologies. Additionally, histopathological and sectoral proteomic analysis of amyloid deposits, found in some mitral and aortic valves, from the second experiment, were also reported. Results Mitral rheumatic valves exhibited higher expression of genes linked to calcification and immuno-inflammation compared to aortic rheumatic valves (Figure 1). Proteomic analysis, visualized through PCA graphs, highlighted differences in proteomic patterns. Despite having the same genetic pattern, control valves exhibited different proteomic profiles (Figure 1) Rheumatic mitral and aortic valves, even from the same individual, showed distinct proteomic fingerprint (Figure 1). A total of 49 significant proteins were identified in distinguishing healthy mitral and aortic valves from the same individual (Figure 1). The aortic valve displayed a richer extracellular matrix and higher levels of housekeeping proteins that maintain valve homeostasis compared to the mitral valve (Figure 1). The dominant proteomic pattern in valvular rheumatic disease was identified as alterations in critical mitochondrial metabolic activities related to proteostasis. (Figure 2). Particularly notable was the upregulation of pathways associated with lipid metabolism (Figure 2). Finally, amyloid deposits suggested APOA1 as a potential deposit protein in RHD (Figure 2). Conclusion The study confirms distinct constitutional differences between mitral and aortic valves affecting rheumatic disease progression. It emphasizes the role of altered proteostasis and altered proteins deposit, mitochondrial metabolic changes, and inflammatory responses in the disease's pathophysiology, highlighting the complexity of valvular rheumatic disease involvement.For the first time amyloid deposition has been reported as a likely consequence of significant disruption in valvular proteostasis and the proteins potentially comprising this deposit within a rheumatic valve.Genomic and proteomic overviewproteomic fingerprint of RHD and amyloid

Cytotoxicity and mechanisms of perfluorobutane sulfonate (PFBS) in umbilical cord fibroblast cells of Yangtze finless porpoise

Cytotoxicity and mechanisms of perfluorobutane sulfonate (PFBS) in umbilical cord fibroblast cells of Yangtze finless porpoise

OCT1 (SLC22A1) transporter kinetics and regulation in primary human hepatocyte 3D spheroids

3D spheroids of primary human hepatocytes (3D PHH) retain a differentiated phenotype with largely conserved metabolic function and proteomic fingerprint over weeks in culture. As a result, 3D PHH are gaining importance as a model for mechanistic liver homeostasis studies and in vitro to in vivo extrapolation (IVIVE) in drug discovery. However, the kinetics and regulation of drug transporters have not yet been assessed in 3D PHH. Here, we used organic cation transporter 1 (OCT1/SLC22A1) as a model to study both transport kinetics and the long-term regulation of transporter activity via relevant signalling pathways. The kinetics of the OCT1 transporter was studied using the fluorescent model substrate 4-(4-(dimethylamino)styryl)-N-methylpyridinium (ASP+) and known OCT1 inhibitors in individual 3D PHH. For long-term studies, 3D PHH were treated with xenobiotics for seven days, after which protein expression and OCT1 function were assessed. Global proteomic analysis was used to track hepatic phenotypes as well as prototypical changes in other regulated proteins, such as P-glycoprotein and Cytochrome P450 3A4. ASP+ kinetics indicated a fully functional OCT1 transporter with a Km value of 14 ± 4.0µM as the mean from three donors. Co-incubation with known OCT1 inhibitors decreased the uptake of ASP+ in the 3D PHH spheroids by 35–52%. The long-term exposure studies showed that OCT1 is relatively stable upon activation of nuclear receptor signalling or exposure to compounds that could induce inflammation, steatosis or liver injury. Our results demonstrate that 3D PHH spheroids express physiologically relevant levels of fully active OCT1 and that its transporter kinetics can be accurately studied in the 3D PHH configuration. We also confirm that OCT1 remains stable and functional during the activation of key metabolic pathways that alter the expression and function of other drug transporters and drug-metabolizing enzymes. These results will expand the range of studies that can be performed using 3D PHH.

Exploratory Mass Spectrometry of Cerebrospinal Fluid from Persons with Autopsy-Confirmed LATE-NC.

Common neuropathologies associated with dementia include Alzheimer's disease neuropathologic change (ADNC) and limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC). Biofluid proteomics provides a window into the pathobiology of dementia and the information from biofluid tests may help guide clinical management. Participants (n = 29) had been autopsied and had antemortem CSF draws in a longitudinal cohort of older adults at the University of Kentucky AD Research Center. Cases were designated as LATE-NC + if they had LATE-NC stage > 1 (n = 9); the remaining 20 cases were designated LATE-NC-. This convenience sample of CSF specimens was analyzed in two separate processes: From one group, aliquots were depleted of highly abundant proteins using affinity spin columns. Tryptic digests of sample proteins were subjected to liquid chromatographic separation and mass spectrometry. Relative quantification was performed using Sciex software. Peptides referent to a total of 949 proteins were identified in the samples depleted of abundant proteins, and 820 different proteins were identified in the non-depleted samples. When the Bonferroni/false-discovery statistical correction was applied to account for having made multiple comparison tests, only 4 proteins showed differential expression (LATE-NC + vs LATE-NC-) in the non-depleted samples (RBP4, MIF, IGHG3, and ITM2B). Post hoc western blots confirmed that RBP4 expression was higher in the LATE-NC + cases at the group level. In summary, an exploratory assessment of proteomes of autopsy-confirmed LATE-NC and non-LATE-NC CSF did not demonstrate a clear-cut proteomic fingerprint that distinguished the two groups. There was, however, an increase in RBP4 protein levels in CSF from LATE-NC cases.

Very short sleep duration reveals a proteomic fingerprint that is selectively associated with incident diabetes mellitus but not with incident coronary heart disease: a cohort study

BackgroundThe molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease.MethodsWe assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46–68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates.ResultsSixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06–1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD.ConclusionsWe here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

Predicting Cellular Rejection of Renal Allograft Based on the Serum Proteomic Fingerprint.

Kidney transplantation is an essential medical procedure that significantly enhances the survival rates and quality of life for patients with end-stage kidney disease. However, despite advancements in immunosuppressive therapies, allograft rejection remains a leading cause of organ loss. Notably, predictions of cellular rejection processes primarily rely on biopsy analysis, which is not routinely performed due to its invasive nature. The present work evaluates if the serum proteomic fingerprint, as acquired by Fourier Transform Infrared (FTIR) spectroscopy, can predict cellular rejection processes. We analyzed 28 serum samples, corresponding to 17 without cellular rejection processes and 11 associated with cellular rejection processes, as based on biopsy analyses. The leave-one-out-cross validation procedure of a Naïve Bayes model enabled the prediction of cellular rejection processes with high sensitivity and specificity (AUC > 0.984). The serum proteomic profile was obtained in a high-throughput mode and based on a simple, rapid, and economical procedure, making it suitable for routine analyses and large-scale studies. Consequently, the current method presents a high potential to predict cellular rejection processes translatable to clinical scenarios, and that should continue to be explored.

A universal tool for marine metazoan species identification: towards best practices in proteomic fingerprinting

Proteomic fingerprinting using MALDI-TOF mass spectrometry is a well-established tool for identifying microorganisms and has shown promising results for identification of animal species, particularly disease vectors and marine organisms. And thus can be a vital tool for biodiversity assessments in ecological studies. However, few studies have tested species identification across different orders and classes. In this study, we collected data from 1246 specimens and 198 species to test species identification in a diverse dataset. We also evaluated different specimen preparation and data processing approaches for machine learning and developed a workflow to optimize classification using random forest. Our results showed high success rates of over 90%, but we also found that the size of the reference library affects classification error. Additionally, we demonstrated the ability of the method to differentiate marine cryptic-species complexes and to distinguish sexes within species.

Plasma proteome fingerprint in kidney diseases.

Kidney diseases pose a serious healthcare problem because of their high prevalence, worsening of patients' quality of life, and high mortality. Patients with kidney diseases are often asymptomatic until disease progression starts. Expensive renal replacement therapy options, such as dialysis or kidney transplant, are required for end-stage kidney disease. Early diagnosis of kidney pathology is crucial for slowing down or curbing further damage. This study aimed to analyze the features of the protein composition of blood plasma in patients with the most common kidney pathologies: kidney calculus, kidney cyst, and kidney cancer. The study involved 75 subjects. Proteins associated with kidney pathologies (CFB, SERPINA3, HPX, HRG, SERPING1, HBB, ORM2, and CP) were proposed. These proteins are important participants of complement and coagulation cascade activation and lipid metabolism. The revealed phosphorylated proteoforms (CFB, C4A/C4B, F2, APOB, TTR, and NRAP) were identified. For them, modification sites were mapped on 3D protein models, and the potential role in formation of complexes with native partner proteins was assessed. The study demonstrates that the selected kidney pathologies have a similar proteomic profile, and patients can be classified into kidney pathology groups with an accuracy of (70-80)%.

The proteomic landscape of sperm surface deciphers its maturational and functional aspects in buffalo.

Buffalo is a dominant dairy animal in many agriculture-based economies. However, the poor reproductive efficiency (low conception rate) of the buffalo bulls constrains the realization of its full production potential. This in turn leads to economic and welfare issues, especially for the marginal farmers in such economies. The mammalian sperm surface proteins have been implicated in the regulation of survival and function of the spermatozoa in the female reproductive tract (FRT). Nonetheless, the lack of specific studies on buffalo sperm surface makes it difficult for researchers to explore and investigate the role of these proteins in the regulation of mechanisms associated with sperm protection, survival, and function. This study aimed to generate a buffalo sperm surface-specific proteomic fingerprint (LC-MS/MS) and to predict the functional roles of the identified proteins. The three treatments used to remove sperm surface protein viz. Elevated salt, phosphoinositide phospholipase C (PI-PLC) and in vitro capacitation led to the identification of N = 1,695 proteins (≥1 high-quality peptide-spectrum matches (PSMs), p < 0.05, and FDR<0.01). Almost half of these proteins (N = 873) were found to be involved in crucial processes relevant in the context of male fertility, e.g., spermatogenesis, sperm maturation and protection in the FRT, and gamete interaction or fertilization, amongst others. The extensive sperm-surface proteomic repertoire discovered in this study is unparalleled vis-à-vis the depth of identification of reproduction-specific cell-surface proteins and can provide a potential framework for further studies on the functional aspects of buffalo spermatozoa.

Transcriptomic and proteomic fingerprints induced by the fungicides difenoconazole and metalaxyl in zebrafish embryos

In this study, we applied OMICs analysis to identify substance-specific biomarker candidates, which may act as early indicators for specific ecotoxic modes of actions (MoA). Zebrafish embryos were exposed to two sublethal concentrations of difenoconazole and metalaxyl according to a modified protocol of the OECD test guideline No. 236. At the end of exposure, total RNA and protein were extracted, followed by transcriptomics and proteomics analysis. The analysis of significantly differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) revealed a positive exposure-response correlation in all test concentrations for both fungicides. Similarly, also a positive correlation between the obtained transcriptome and proteome data was observed, highlighting the robustness of our approach. From the detected DEGs, candidate biomarkers specific for difenoconazole (apoa1b, gatm, mylpfb and acta1b) and metalaxyl (lgals2b, abat, fabp1b.1 and myh9a) were selected, and their biological functions were discussed to assess the predictive potential.

The proteomic fingerprint in infants with single ventricle heart disease in the interstage period: evidence of chronic inflammation and widespread activation of biological networks.

Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time, with 70% of patients experiencing acute kidney injury, 33% neurodevelopmental impairment, 14% growth failure, and 5.5% of patients suffering necrotizing enterocolitis. Proteomics is a method to identify new biomarkers and mechanisms of injury in complex physiologic states. Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at -80°C, and run on a panel of 1,500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR <0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. PLS-DA readily discriminated between SVHD cases (n = 33) and controls (n = 24) based on their proteomic pattern alone (Accuracy = 0.96, R2 = 0.97, Q2 = 0.80). 568 proteins differed between groups (FDR <0.05). We identified 25 up-regulated functional clusters and 13 down-regulated. Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neural development, gastrointestinal system, and cardiac physiology and development. We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with >500 circulating proteins distinguishing the groups. These proteomic data identify widespread protein dysregulation across multiple biologic systems with promising biological plausibility as drivers of SVHD morbidity.

Abstract 17103: The Proteomic Fingerprint in Patients With Single Ventricle Disease in the Interstage Period: Evidence of Chronic Inflammation and Widespread Activation of Biological Networks

Introduction: Children with single ventricle heart disease (SVHD) experience significant morbidity across systems and time: (AKI 70%, neurodevelopmental impairment 33%, growth failure 14%, NEC 5.5%). Proteomics is a novel method to identify new biomarkers and mechanisms of injury in complex physiologic states. Hypothesis: Does the proteome of patients with SVHD differ from healthy children, and which biological systems are activated or repressed? Methods: Infants with SVHD in the interstage period were compared to similar-age healthy controls. Serum samples were collected, stored at -80C, and run on a panel of 1500 proteins in single batch analysis (Somalogic Inc., CO). Partial Least Squares-Discriminant Analysis (PLS-DA) was used to compare the proteomic profile of cases and controls and t-tests to detect differences in individual proteins (FDR &lt; 0.05). Protein network analysis with functional enrichment was performed in STRING and Cytoscape. Results: PLS-DA readily discriminated between cases (n=33) and controls (n=24) based on their proteomic pattern alone (Accuracy=0.96, R2=0.97, Q2=0.80) (Fig 1a). 568 proteins differed between groups (FDR &lt; 0.05). The 15 proteins with the greatest effect on the proteomic phenotype between the groups are shown (Fig 1b). We identified 25 up-regulated functional clusters and 13 down-regulated (5 clusters highlighted in Fig 1c). Active biological systems fell into six key groups: angiogenesis and cell proliferation/turnover, immune system activation and inflammation, altered metabolism, neuronal development, gastrointestinal system, and cardiac development. Conclusions: We report a clear differentiation in the circulating proteome of patients with SVHD and healthy controls with &gt;500 circulating proteins distinguishing the groups. This proteomic data identifies various dysregulated protein networks across multiple organ systems with promising biological plausibility as drivers of SVHD morbidity.

Preomic profile of BxPC-3 cells after treatment with BRC4

Preomic profile of BxPC-3 cells after treatment with BRC4

Potential of MALDI-TOF MS-based proteomic fingerprinting for species identification of Cnidaria across classes, species, regions and developmental stages.

Morphological identification of cnidarian species can be difficult throughout all life stages due to the lack of distinct morphological characters. Moreover, in some cnidarian taxa genetic markers are not fully informative, and in these cases combinations of different markers or additional morphological verifications may be required. Proteomic fingerprinting based on MALDI-TOF mass spectra was previously shown to provide reliable species identification in different metazoans including some cnidarian taxa. For the first time, we tested the method across four cnidarian classes (Staurozoa, Scyphozoa, Anthozoa, Hydrozoa) and included different scyphozoan life-history stages (polyp, ephyra, medusa) in our dataset. Our results revealed reliable species identification based on MALDI-TOF mass spectra across all taxa with species-specific clusters for all 23 analysed species. In addition, proteomic fingerprinting was successful for distinguishing developmental stages, still by retaining a species specific signal. Furthermore, we identified the impact of different salinities in different regions (North Sea and Baltic Sea) on proteomic fingerprints to be negligible. In conclusion, the effects of environmental factors and developmental stages on proteomic fingerprints seem to be low in cnidarians. This would allow using reference libraries built up entirely of adult or cultured cnidarian specimens for the identification of their juvenile stages or specimens from different geographic regions in future biodiversity assessment studies.

How eluents define proteomic fingerprinting of protein corona on nanoparticles

How eluents define proteomic fingerprinting of protein corona on nanoparticles

Cyanide Biodegradation by a Native Bacterial Consortium and Its Potential for Goldmine Tailing Biotreatment

A native cyanide-degrading bacterial consortium was isolated from goldmine tailing sediments. Mine tailings are toxic effluents due to their metal–cyanide complexes. The bacterial consortium was able to degrade an initial sodium cyanide concentration ranging from 5 to 120 mg L−1 in alkaline synthetic wastewater (pH &gt; 9.2), for a maximum of 15 days. The free cyanide biodegradation efficiency was 98% for the highest initial free cyanide concentration tested and followed a first-order kinetic profile, with an estimated kinetic rate constant of 0.12 ± 0.011 d−1. The cyanide-degrading consortium was streaked with serial dilutions on a specific medium (R2A). 16S rRNA gene sequencing and mass spectrometry proteomic fingerprinting of the isolates showed that the bacterial strains belonged to Microbacterium paraoxydans, Brevibacterium casei, Brevundimonas vesicularis, Bacillus cereus and Cellulosimicrobium sp. The first four genera had previously been identified as cyanide-degrading bacteria. Microbacterium and Brevibacterium had previously been found in alkaline conditions, showing resistance to heavy metals. As for Cellulosimicrobium, to our knowledge, this is the first study to implicate it directly or indirectly in cyanide biodegradation. In this research, these genera were identified as functional bacteria for cyanide degradation, and they might be suitable for mine tailing biotechnological tertiary treatment.

Robust Acute Pancreatitis Identification and Diagnosis: RAPIDx

The occurrence of acute pancreatitis (AP) is increasing significantly worldwide. However, current diagnostic methods of AP do not provide a clear clinical stratification of severity, and the prediction of complications in AP is still limited. Here, we present a robust AP identification and diagnosis (RAPIDx) method by the proteomic fingerprinting of intact nanoscale extracellular vesicles (EVs) from clinical samples. By tracking analysis of circulating biological nanoparticles released by cells (i.e., EVs) via bottom-up proteomics, we obtain close phenotype connections between EVs, cell types, and multiple tissues based on their specific proteomes and identify the serum amyloid A (SAA) proteins on EVs as potential biomarkers that are differentially expressed from AP patients significantly. We accomplish the quantitative analysis of EVs fingerprints using MALDI-TOF MS and find the SAA proteins (SAA1-1, desR-SAA1-2, SAA2, SAA1-2) with areas under the curve (AUCs) from 0.92 to 0.97, which allows us to detect AP within 30 min. We further realize that SAA1-1 and SAA2, combined with two protein peaks (5290.19, 14032.33 m/z), can achieve an AUC of 0.83 for classifying the severity of AP. The RAPIDx platform will facilitate timely diagnosis and treatment of AP before severity development and persistent organ failure and promote precision diagnostics and the early diagnosis of pancreatic cancer.