Proteomic discovery of chemical probes that perturb protein complexes in human cells.

Most human proteins lack chemical probes, and several large-scale and generalizable small-molecule binding assays have been introduced to address this problem. How compounds discovered in such "binding-first" assays affect protein function, nonetheless, often remains unclear. Here, we describe a "function-first" proteomic strategy that uses size exclusion chromatography (SEC) to assess the global impact of electrophilic compounds on protein complexes in human cells. Integrating the SEC data with cysteine-directed activity-based protein profiling identifies changes in protein-protein interactions that are caused by site-specific liganding events, including the stereoselective engagement of cysteines in PSME1 and SF3B1 that disrupt the PA28 proteasome regulatory complex and stabilize a dynamic state of the spliceosome, respectively. Our findings thus show how multidimensional proteomic analysis of focused libraries of electrophilic compounds can expedite the discovery of chemical probes with site-specific functional effects on protein complexes in human cells.

Identification and characterization of transition metal-binding proteins and metabolites in the phloem sap of Brassica napus.

Transition metal (TM) distribution through the phloem is an essential part of plant metabolism and is required for systemic signaling and balancing source-to-sink relationships. Due to their reactivity, TMs are expected to occur in complexes within the phloem sap; however, metal speciation in the phloem sap remains largely unexplored. Here, we isolated phloem sap from Brassica napus and analyzed it via size exclusion chromatography coupled online to sector-field ICP-MS. Our data identified known TM-binding proteins and molecules including metallothioneins (MT), glutathione, and nicotianamine. While the main peak of all metals was low MW (∼1.5 kD), additional peaks ∼10 to 15 kD containing Cu, Fe, S, and Zn were also found. Further physicochemical analyses of MTs with and without affinity tags corroborated that MTs can form complexes of diverse molecular weights. We also identified and characterized potential artifacts in the TM-biding ability of B. napus MTs between tagged and non-tagged MTs. That is, the native BnMT2 binds Zn, Cu, and Fe, while MT3a and MT3b only bind Cu and Zn. In contrast, his-tagged MTs bind less Cu and were found to bind Co and Mn and aggregated to oligomeric forms to a greater extent compared to the phloem sap. Our data indicates that TM chemistry in the phloem sap is more complex than previously anticipated and that more systematic analyses are needed to establish the precise speciation of TM and TM-ligand complexes within the phloem sap.

In vitro higher-order oligomeric assembly of the respiratory syncytial virus M2-1 protein with longer RNAs.

The respiratory syncytial virus (RSV) M2-1 protein is a transcriptional antitermination factor crucial for efficiently synthesizing multiple full-length viral mRNAs. During RSV infection, M2-1 exists in a complex with mRNA within cytoplasmic compartments called inclusion body-associated granules (IBAGs). Prior studies showed that M2-1 can bind along the entire length of viral mRNAs instead of just gene-end (GE) sequences, suggesting that M2-1 has more sophisticated RNA recognition and binding characteristics. Here, we analyzed the higher oligomeric complexes formed by M2-1 and RNAs in vitro using size exclusion chromatography (SEC), electrophoretic mobility shift assays (EMSA), negative stain electron microscopy (EM), and mutagenesis. We observed that the minimal RNA length for such higher oligomeric assembly is about 14 nucleotides for polyadenine sequences, and longer RNAs exhibit distinct RNA-induced binding modality to M2-1, leading to enhanced particle formation frequency and particle homogeneity as the local RNA concentration increases. We showed that particular cysteine residues of the M2-1 cysteine-cysteine-cystine-histidine (CCCH) zinc-binding motif are essential for higher oligomeric assembly. Furthermore, complexes assembled with long polyadenine sequences remain unaffected when co-incubated with ribonucleases or a zinc chelation agent. Our study provided new insights into the higher oligomeric assembly of M2-1 with longer RNA.IMPORTANCERespiratory syncytial virus (RSV) causes significant respiratory infections in infants, the elderly, and immunocompromised individuals. The virus forms specialized compartments to produce genetic material, with the M2-1 protein playing a pivotal role. M2-1 acts as an anti-terminator in viral transcription, ensuring the creation of complete viral mRNA and associating with both viral and cellular mRNA. Our research focuses on understanding M2-1's function in viral mRNA synthesis by modeling interactions in a controlled environment. This approach is crucial due to the challenges of studying these compartments in vivo. Reconstructing the system in vitro uncovers structural and biochemical aspects and reveals the potential functions of M2-1 and its homologs in related viruses. Our work may contribute to identifying targets for antiviral inhibitors and advancing RSV infection treatment.

Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum.

Extracellular vesicles (EVs) are important players in melanoma progression, but their use as clinical biomarkers has been limited by the difficulty of profiling blood-derived EV proteins with high depth of coverage, the requirement for large input amounts, and complex protocols. Here, we provide a streamlined and reproducible experimental workflow to identify plasma- and serum- derived EV proteins of healthy donors and melanoma patients using minimal amounts of sample input. SEC-DIA-MS couples size-exclusion chromatography to EV concentration and deep-proteomic profiling using data-independent acquisition. From as little as 200 µL of plasma per patient in a cohort of three healthy donors and six melanoma patients, we identified and quantified 2896 EV-associated proteins, achieving a 3.5-fold increase in depth compared to previously published melanoma studies. To compare the EV-proteome to unenriched blood, we employed an automated workflow to deplete the 14 most abundant proteins from plasma and serum and thereby approximately doubled protein group identifications versus native blood. The EV proteome diverged from corresponding unenriched plasma and serum, and unlike the latter, separated healthy donor and melanoma patient samples. Furthermore, known melanoma markers, such as MCAM, TNC, and TGFBI, were upregulated in melanoma EVs but not in depleted melanoma plasma, highlighting the specific information contained in EVs. Overall, EVs were significantly enriched in intact membrane proteins and proteins related to SNARE protein interactions and T-cell biology. Taken together, we demonstrated the increased sensitivity of an EV-based proteomic workflow that can be easily applied to larger melanoma cohorts and other indications.

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis.

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 µL of human plasma in 15 min. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals who underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

Filling the gaps in peptide maps with a platform assay for top-down characterization of purified protein samples.

Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.

Effect of the 35 nm and 70 nm Size Exclusion Chromatography (SEC) Column and Plasma Storage Time on Separated Extracellular Vesicles.

The technical difficulty of separating extracellular vesicles (EVs) from plasma proteins in human blood presents a significant hurdle in EV research, particularly during nano ultra-high-performance liquid chromatography-tandem mass spectrometric (UHPLC-MS/MS) analysis, where detecting "vesicular" proteins among abundant plasma proteins is challenging. Standardisation is a pressing issue in EV research, prompting collaborative global efforts to address it. While the MISEV guidelines offer valuable recommendations, unanswered questions remain, particularly regarding sample storage. We compared size exclusion chromatography (SEC) columns with pore sizes of 35 nm and 70 nm to identify fractions with minimal contaminating proteins and the highest concentration of small EVs (sEVs). Following column selection, we explored potential differences in the quality and quantity of sEVs isolated from platelet-free plasma (PFP) after long-term storage at -80 °C (>2.5 years) compared to freshly drawn blood. Our methodologically rigorous study indicates that prolonged storage, under correct storage and processing conditions, does not compromise sEV quality. Both columns effectively isolated vesicles, with the 70 nm column exhibiting a higher abundance of "vesicular" proteins. We propose a relatively rapid and moderately efficient protocol for obtaining a comparatively pure sEV fraction from plasma, facilitating sEV processing in clinical trials.

Comparing the Proteomic Profiles of Extracellular Vesicles Isolated using Different Methods from Long-term Stored Plasma Samples.

BACKGROUND: The lack of standardized protocols for isolating extracellular vesicles (EVs), especially from biobank-stored blood plasma, translates to limitations for the study of new biomarkers. This study examines whether a combination of current isolation methods could enhance the specificity and purity of isolated EVs for diagnosis and personalized medicine purposes. RESULTS: EVs were isolated from healthy human plasma stored for one year by ultracentrifugation (UC), size exclusion chromatography (SEC), or SEC and UC combined (SEC + UC). The EV isolates were then characterized by transmission electron microscopy imaging, nanoparticle tracking analysis (NTA) and western blotting. Proteomic procedures were used to analyze protein contents. The presence of EV markers in all isolates was confirmed by western blotting yet this analysis revealed higher albumin expression in EVs-UC, suggesting plasma protein contamination. Proteomic analysis identified 542 proteins, SEC + UC yielding the most complex proteome at 364 proteins. Through gene ontology enrichment, we observed differences in the cellular components of EVs and plasma in that SEC + UC isolates featured higher proportions of EV proteins than those derived from the other two methods. Analysis of proteins unique to each isolation method served to identify 181 unique proteins for the combined approach, including those normally appearing in low concentrations in plasma. This indicates that with this combined method, it is possible to detect less abundant plasma proteins by proteomics in the resultant isolates. CONCLUSIONS: Our findings reveal that the SEC + UC approach yields highly pure and diverse EVs suitable for comprehensive proteomic analysis with applications for the detection of new biomarkers in biobank-stored plasma samples.

Surfactant Micelle-Driven High-Efficiency and High-Resolution Length Separation of Carbon Nanotubes for Electronic Applications.

High-efficiency extraction of long single-wall carbon nanotubes (SWCNTs) with excellent optoelectronic properties from SWCNT solution is critical for enabling their application in high-performance optoelectronic devices. Here, a straightforward and high-efficiency method is reported for length separation of SWCNTs by modulating the concentrations of binary surfactants. The results demonstrate that long SWCNTs can spontaneously precipitate for binary-surfactant but not for single-surfactant systems. This effect is attributed to the formation of compound micelles by binary surfactants that squeeze the free space of long SWCNTs due to their large excluded volumes. With this technique, it can readily separate near-pure long (≥500 nm in length, 99% in content) and short (≤500 nm in length, 98% in content) SWCNTs with separation efficiencies of 26% and 64%, respectively, exhibiting markedly greater length resolution and separation efficiency than those of previously reported methods. Thin-film transistors fabricated from extracted semiconducting SWCNTs with lengths >500 nm exhibit significantly improved electrical properties, including a 10.5-fold on-state current and 14.7-fold mobility, compared with those with lengths <500 nm. The present length separation technique is perfectly compatible with various surfactant-based methods for structure separations of SWCNTs and is significant for fabrication of high-performance electronic and optoelectronic devices.

Profiling Small RNA From Brain Extracellular Vesicles in Individuals With Depression.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability with significant mortality risk. Despite progress in our understanding of the etiology of MDD, the underlying molecular changes in the brain remain poorly understood. Extracellular vesicles (EVs) are lipid-bound particles that can reflect the molecular signatures of the tissue of origin. We aimed to optimize a streamlined EV isolation protocol from postmortem brain tissue and determine whether EV RNA cargo, particularly microRNAs (miRNAs), have an MDD-specific profile. METHODS: EVs were isolated from postmortem human brain tissue. Quality was assessed using western blots, transmission electron microscopy, and microfluidic resistive pulse sensing. EV RNA was extracted and sequenced on Illumina platforms. Functional follow-up was performed in silico. RESULTS: Quality assessment showed an enrichment of EV markers, as well as a size distribution of 30 to 200 nm in diameter, and no contamination with cellular debris. Small RNA profiling indicated the presence of several RNA biotypes, with miRNAs and transfer RNAs being the most prominent. Exploring miRNA levels between groups revealed decreased expression of miR-92a-3p and miR-129-5p, which was validated by qPCR and was specific to EVs and not seen in bulk tissue. Finally, in silico functional analyses indicate potential roles for these 2 miRNAs in neurotransmission and synaptic plasticity. CONCLUSION: We provide a streamlined isolation protocol that yields EVs of high quality that are suitable for molecular follow-up. Our findings warrant future investigations into brain EV miRNA dysregulation in MDD.

Biochemical characterization of a high affinity phosphate transporter (PiPT) from root endophyte fungus Piriformospora indica.

We have functionally characterized the high-affinity phosphate transporter (PiPT) from the root endophyte fungus Piriformospora indica. PiPT belongs to the major facilitator superfamily (MFS). PiPT protein was purified by affinity chromatography (Ni-NTA) and Size Exclusion Chromatography (SEC). The functionality of solubilized PiPT was determined in detergent-solubilized state by fluorescence quenching and in proteoliposomes. In the fluorescence quenching assay, PiPT exhibited a saturation concentration of approximately 2 µM, at a pH of 4.5. Proteoliposomes of size 121.6 nm radius, showed transportation of radioactive phosphate. Vmax was measured to be 232.2 ± 11 pmol/min/mg protein. We have found Km to be 45.8 ± 6.2 µM suggesting high affinity towards phosphate.

A Novel Size Exclusion Chromatography Method for the Analysis of Monoclonal Antibodies and Antibody-drug Conjugates by Using Sodium Iodide in the Mobile Phase.

PURPOSES: Size exclusion chromatography (SEC) is widely used to characterize molecular size variants of antibody drugs. However, SEC analysis is hindered by secondary interactions (or nonspecific interactions) between proteins and stationary phase packing, which result in poor column efficiency. Previous studies have reported that chaotropic salt can inhibit these interactions, but the corresponding applications of this aspect are relatively rare. Therefore, this study introduces a novel approach using sodium iodide (NaI) as a mobile-phase component in SEC and investigates the influence of the mobile-phase composition on secondary interactions. METHODS: SEC analysis was performed on one antibody-drug conjugate and four monoclonal antibodies (mAbs) using three different mobile-phase systems (i.e., sodium chloride/L-arginine hydrochloride/NaI mobile phases system) to compare the column efficiency. Subsequently, mAb-1 was used as a model to investigate the effects of these factors on secondary interactions by adjusting the ionic strength (salt concentration) and pH of the NaI mobile-phase system. RESULTS: NaI exhibits superior column efficiency performance in the SEC analysis of most products. The ionic strength will affect nonideal electrostatic and hydrophobic interaction. An appropriate ionic strength can inhibit electrostatic interactions, while an excessive ionic strength increases hydrophobic interactions. pH primarily influences electrostatic interactions. Determining the appropriate pH necessitates consideration of the isoelectric point of the protein and the pH tolerance of the column. CONCLUSIONS: In SEC analysis, using NaI as the salt component in the mobile phase reduces secondary interactions and improves column efficiency. This approach is advantageous for samples with intense secondary interactions and is a suitable alternative.

Influence of Fuel Properties on the Light Absorption of Fresh and Laboratory-Aged Atmospheric Brown Carbon Produced from Realistic Combustion of Boreal Peat and Spruce Foliage.

Climate change has exacerbated fire activity in the boreal region. Consequently, smoldering boreal peatland fires are an increasingly important source of light-absorbing atmospheric organic carbon ("brown carbon"; BrC). To date, however, BrC from this source remains largely unstudied, which limits our ability to predict its climate impact. Here, we use size-exclusion chromatography coupled with diode array UV-vis detection to examine the molecular-size-dependent light absorption properties of fresh and photoaged aqueous BrC extracts collected during laboratory combustion of boreal peat and live spruce foliage. The atmospheric stability of BrC extracts varies with chromophore molecular size and fuel type: in particular, the high-molecular-weight fractions of both peat- and spruce-BrC are more resistant to photobleaching than their corresponding low-molecular-weight fractions, and total light absorption by peat-BrC persists over longer illumination timescales than that of spruce-BrC. Importantly, the BrC molecular size distribution itself varies with fuel properties (e.g., moisture content) and to an even greater extent with fuel type. Overall, our findings suggest that the accurate estimation of BrC radiative forcing, and the overall climate impact of wildfires, will require atmospheric models to consider the impact of regional diversity in vegetation/fuel types.

Optimized procedure for high-throughput transcriptome profiling of small extracellular vesicles isolated from low volume serum samples.

OBJECTIVES: Small extracellular vesicles (EVs) contain various signaling molecules, thus playing a crucial role in cell-to-cell communication and emerging as a promising source of biomarkers. However, the lack of standardized procedures impedes their translation to clinical practice. Thus, we compared different approaches for high-throughput analysis of small EVs transcriptome. METHODS: Small EVs were isolated from 150 µL of serum. Quality and quantity were assessed by dynamic light scattering, transmission electron microscopy, and Western blot. Comparison of RNA extraction efficiency was performed, and expression of selected genes was analyzed by RT-qPCR. Whole transcriptome analysis was done using microarrays. RESULTS: Obtained data confirmed the suitability of size exclusion chromatography for isolation of small EVs. Analyses of gene expression showed the best results in case of samples isolated by Monarch Total RNA Miniprep Kit. Totally, 7,182 transcripts were identified to be deregulated between colorectal cancer patients and healthy controls. The majority of them were non-coding RNAs with more than 70 % being lncRNAs, while protein-coding genes represented the second most common gene biotype. CONCLUSIONS: We have optimized the protocol for isolation of small EVs and their RNA from low volume of sera and confirmed the suitability of Clariom D Pico Assays for transcriptome profiling.

Physical origin of the peak tailing of monoclonal antibodies in size-exclusion chromatography using bio-compatible systems and columns.

The analysis of mixtures containing monoclonal antibody (mAb) (approximately 150 kDa molecular weight) and sub-unit impurities (approximately 100 kDa) is challenging, even when adopting the latest ultra-high-pressure liquid chromatography (UHPLC) columns (4.6 mm [Formula: see text] 150 mm coated hardware, 1.7 [Formula: see text]m 250 BEH[Formula: see text] Surface-modified Particles) and systems (ACQUITY[Formula: see text] UPLC[Formula: see text] I-class Bio Plus). The main issue still encountered is a persistent tail of the mAb peak. Here, the physical origin(s) of such peak tailing in size-exclusion chromatography (SEC) are investigated from both fundamental and practical approaches. Up to five relevant physical origins are analyzed: sample heterogeneity (glycoforms), UHPLC system dispersion, strong residual binding of the mAb to the SEC particles (via hydrophobic and/or electrostatic interactions) and to the stainless steel column/system hardware, slow escape kinetics of the mAb from the SEC particles, and flow heterogeneity caused by the non-ideal slurry packing of SEC columns. Experiments (testing sample heterogeneity, system dispersion, and strong residual interactions) and calculations (predicting the transient absorption/escape kinetics in a single SEC particle and the two-dimensional peak concentration profiles) altogether unambiguously demonstrate that the observed mAb peak tailing is caused primarily by the long-range velocity biases across the SEC column combined with the slow transverse dispersion of mAbs. Therefore, improvement in the resolution between mAb and sub-unit fragment impurities can only be achieved by increasing the column length, e.g., by applying recycling chromatography at acceptable pressures.

Nasal exudate for diagnosis of stroke: fundamental studies through iron fractionation, total iron, and targeted protein determinations.

During the last years, there has been an increasing research interest in the analysis of biological fluids requiring non-invasive sampling for biomedical and clinical applications. In this work, we have focused on the nasal exudate with the aim of investigating the potential use of this fluid to know the role of iron in stroke and also for diagnosis. Potential differences in the nasal exudate, collected in swabs, from diagnosed hemorrhagic stroke, ischemic stroke, and control groups were investigated with regard to total iron by inductively coupled plasma-mass spectrometry, iron fractionation studies by size exclusion chromatography together with post-column isotope dilution analysis, and four proteins containing iron (ferritin, transferrin, lactoferrin, and ferroportin) with ELISA kits. All these analyses represent an analytical challenge, considering the rather limited amount of sample (10-40 mg) available, being the nasal exudate extracted from the swab with 300 µL 10 mM Tris/HCl, pH = 7.4. Studies to obtain reliable analytical information, such as the blank contribution of the sampling step, evaluation of the extraction efficiency of the nasal exudate from the swab, and normalization strategies for data treatment, have been carried out. Results showed that despite the limited number of investigated samples, fractionation studies as well as the concentrations of ferritin and ferroportin obtained with ELISA kits showed a differential behavior between the different cohorts.

Biochemical evaluation and ligand binding studies on glycerophosphodiester phosphodiesterase from Staphylococcus aureus using STD-NMR spectroscopy and molecular docking analysis.

Glycerophosphodiester phosphodiesterase (GDPD) is a highly conserved enzyme in both prokaryotic and eukaryotic organisms. It catalyses the hydrolysis of various glycerophosphodiesters into glycerol-3-phosphate and corresponding alcohols, which serve as building blocks in several biosynthetic pathways. This enzyme is a well-known virulence factor in many pathogenic bacteria, including Staphylococcus aureus, and is thus considered a potential drug target. In this study, competent E. coli BL21(DE3)pLysS expression cells were used to express the GDPD enzyme from vancomycin-resistant Staphylococcus aureus (VRSA), which was then purified using size exclusion and anion exchange chromatography. The hydrolytic activity of GDPD was evaluated on the non-physiological substrate bis(p-nitrophenyl) phosphate (BpNPP), which indicated functional activity of the enzyme. 79 drugs were evaluated for their inhibitory potential against GDPD enzyme by the colorimetric assay. Out of 79 drugs, 13 drugs, including tenofovir (1), adenosine (2), clioquinol (11), bromazepam (12), lamotrigine (13), sulfadiazine (14), azathioprine (15), nicotine (16), sitagliptin PO4 (17), doxofylline (18), clindamycin phosphate (19), gentamycin sulphate (20), and ceftriaxone sodium (21) revealed varying degrees of inhibitory potential with IC50 values in the range of 400 ± 0.007-951 ± 0.016 µM. All drugs were also evaluated for their binding interactions with the target enzyme by saturation transfer difference (STD-NMR) spectroscopy. 10 drugs demonstrated STD interactions and hence, showed binding affinity with the enzyme. Exceptionally, tenofovir (1) was identified to be a better inhibitor with an IC50 value of 400 ± 0.007 µM, as compared to the standard EDTA (ethylenediaminetetraacetic acid) (IC50 = 470 ± 0.008 µM). Moreover, molecular docking studies have identified key interactions of the ligand (tenofovir) with the binding site residues of the enzyme.

The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system.

Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydraulic junction. Herein, we have sampled for a one-year and analyzed the water quality at the hydraulic junction of a dual-source DWDS. The results show that visible changes in drinking water quality, including turbidity, pH, UV254, DOC, residual chlorine, and trihalomethanes (TMHs), are observed at the sample point between 10 and 12 km to one drinking water plant. The average concentration of residual chlorine decreases from 0.74 ± 0.05 mg/L to 0.31 ± 0.11 mg/L during the water supplied from 0 to 10 km and then increases to 0.75 ± 0.05 mg/L at the end of 22 km. Whereas the THMs shows an opposite trend, the concentration reaches to a peak level at hydraulic junction area (10-12 km). According to parallel factor (PARAFAC) and high-performance size-exclusion chromatography (HPSEC) analysis, organic matters vary significantly during water distribution, and tryptophan-like substances and amino acids are closely related to the level of THMs. The hydraulic junction area is confirmed to be located at 10-12 km based on the water quality variation. Furthermore, data-driven models are established by machine learning (ML) with test R2 higher than 0.8 for THMs prediction. And the SHAP analysis explains the model results and identifies the positive (water temperature and water supply distance) and negative (residual chlorine and pH) key factors influencing the THMs formation. This study conducts a deep understanding of water quality at the hydraulic junction areas and establishes predictive models for THMs formation in dual-sources DWDS.

Proteomic analysis of extracellular vesicles derived from canine mammary tumour cell lines identifies protein signatures specific for disease state.

BACKGROUND: Canine mammary tumours (CMT) are among the most common types of tumours in female dogs. Diagnosis currently requires invasive tissue biopsies and histological analysis. Tumour cells shed extracellular vesicles (EVs) containing RNAs and proteins with potential for liquid biopsy diagnostics. We aimed to identify CMT subtype-specific proteome profiles by comparing the proteomes of EVs isolated from epithelial cell lines derived from morphologically normal canine mammary tissue, adenomas, and carcinomas. METHODS: Whole-cell protein lysates (WCLs) and EV-lysates were obtained from five canine mammary cell lines: MTH53A (non-neoplastic); ZMTH3 (adenoma); MTH52C (simple carcinoma); 1305, DT1406TB (complex carcinoma); and their proteins identified by LC-MS/MS analyses. Gene Ontology analysis was performed on differentially abundant proteins from each group to identify up- and down-regulated biological processes. To establish CMT subtype-specific proteomic profiles, weighted gene correlation network analysis (WGCNA) was carried out. RESULTS: WCL and EVs displayed distinct protein abundance signatures while still showing the same increase in adhesion, migration, and motility-related proteins in carcinoma-derived cell lines, and of RNA processing and RNA splicing factors in the adenoma cell line. WGCNA identified CMT stage-specific co-abundant EV proteins, allowing the identification of adenoma and carcinoma EV signatures not seen in WCLs. CONCLUSIONS: EVs from CMT cell lines exhibit distinct protein profiles reflecting malignancy state, allowing us to identify potential biomarkers for canine mammary carcinomas, such as biglycan. Our dataset could therefore potentially serve as a basis for the development of a less invasive clinical diagnostic tool for the characterisation of CMT.

Pseudomorphic synthesis of pore size-tunable mesoporous silica spherical particles and their application for the fraction of low-molecular-weight heparin.

In this study, spherical silica with pore size varied from 30 to 200 Å was synthesized by pseudomorphic transformation at atmospheric pressure. 40-80 Å silica particles with a narrow pore distribution were obtained by using quaternary amine cationic surfactants and different kinds of swelling agents, including polypropylene glycol, 1,3,5-trimethylbenzene, alkanes, and alkanols. Alkyl imidazolium ionic liquid surfactants were used to synthesize large pore size distribution silica spheres with pore sizes in the range of 110-200 Å. All these silica particles can be synthesized under mild conditions within 12 h, which provides a facile synthesis method for the preparation of a chromatographic matrix with tunable pore size. The method is reproducible and the relative standard deviation of silica sphere pore structure parameters in scaled-up preparations is less than 6%. The pore size on the fraction of low-molecular-weight heparin (LMWH) was investigated in size exclusion chromatography. Matrixes with different pore size distributions have various size exclusion regions. By using UPS-60-Diol columns in a twin-column recirculation separation process, LMWH with >85% heparin with molecular weight within the range of 3000-8000 Da were separated in five-column volumes.