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A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead–based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration.

Label-free proteomics by data-dependent acquisition enables the unbiased quantification of thousands of proteins, however it notoriously suffers from high rates of missing values, thus prohibiting consistent protein quantification across large sample cohorts. To solve this, we here present IceR (Ion current extraction Re-quantification), an efficient and user-friendly quantification workflow that combines high identification rates of data-dependent acquisition with low missing value rates similar to data-independent acquisition. Specifically, IceR uses ion current information for a hybrid peptide identification propagation approach with superior quantification precision, accuracy, reliability and data completeness compared to other quantitative workflows. Applied to plasma and single-cell proteomics data, IceR enhanced the number of reliably quantified proteins, improved discriminability between single-cell populations, and allowed reconstruction of a developmental trajectory. IceR will be useful to improve performance of large scale global as well as low-input proteomics applications, facilitated by its availability as an easy-to-use R-package. Label-free quantitative proteomics by data dependent acquisition offers high protein identification rates but is often limited by missing values. Here, the authors develop a quantification workflow that substantially reduces missing values while maintaining high identification rates and quantification accuracy.

High‐throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh‐frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single‐pot solid‐phase‐enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96‐well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands‐on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low‐input samples, reproducibly quantifying 500–1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end‐to‐end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost‐effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non‐clinical applications. Synopsis The study presents an automated sample preparation pipeline for low‐input proteomics based on the SP3 method. The seamless integration of tissue lysis with autoSP3 in a 96‐well format features low variability, high sensitivity and longitudinal reproducibility for clinical studies. An automated, scalable, and cost‐effective workflow (autoSP3) allows reproducible tissue proteomics in a broad range of clinical and non‐clinical applications. Automated tissue lysis is integrated with autoSP3 for an end‐to‐end workflow with minimal manual interference. The workflow allows reduced variability in protein quantification and increased longitudinal reproducibility. Minimal sample losses facilitate low‐input applications in a standardized workflow. Graphical Abstract The study presents an automated sample preparation pipeline for low‐input proteomics based on the SP3 method. The seamless integration of tissue lysis with autoSP3 in a 96‐well format features low variability, high sensitivity and longitudinal reproducibility for clinical studies.

The analysis of proteins that are newly synthesized upon a cellular perturbation can provide detailed insight into the proteomic response that is elicited by specific cues. This can be investigated by pulse-labeling of cells with clickable and stable-isotope-coded amino acids for the enrichment and mass spectrometric characterization of newly synthesized proteins (NSPs), however convoluted protocols prohibit their routine application. Here we report the optimization of multiple steps in sample preparation, mass spectrometry and data analysis, and we integrate them into a semi-automated workflow for the quantitative analysis of the newly synthesized proteome (QuaNPA). Reduced input requirements and data-independent acquisition (DIA) enable the analysis of triple-SILAC-labeled NSP samples, with enhanced throughput while featuring high quantitative accuracy. We apply QuaNPA to investigate the time-resolved cellular response to interferon-gamma (IFNg), observing rapid induction of targets 2 h after IFNg treatment. QuaNPA provides a powerful approach for large-scale investigation of NSPs to gain insight into complex cellular processes. Analysis of newly synthesized proteins upon perturbation can provide detailed insights into immediate proteome remodeling, which drives cellular responses. Here, the authors report an optimized semi-automated workflow for the quantitative analysis of the newly synthesized proteome.

Using agricultural wastes as an alternative phosphorus (P) source has great prospects to improve soil P status. A 70-day incubation experiment was carried out to investigate the effects of superphosphate (SSP), poultry manure (PM), cattle manure (CM), maize straw (MS), and cattle bone meal (CB) with the same total P input on soil P availability and fractions in typical acidic (red soil) and alkaline (fluvo-aquic soil) soils. The results showed that in both fluvo-aquic and red soils, CM out-performed other P sources in improving soil P availability. Changes in soil Olsen-P (ΔOlsen-P) were greater in fluvo-aquic soils with SSP, PM and CM additions than in red soils. Among the different P sources used, only CM has increased the labile soil P fractions to levels similar to that with SSP. Compared with SSP, more monoester P and inositol hexakisphosphate were detected in soils amended with PM and CM. A structural equation model (SEM) analysis suggested that soil pH had a direct positive effect on the labile P fractions in the acidic red soil amended with different P sources. In summary, CM is a superior P source for increasing plant available soil P, with considerable practical implications for P recycling.

Besides human red blood cells (RBC), a standard model used in AFM-single cell force spectroscopy (SCFS), little is known about apparent Young’s modulus (Ea) or adhesion of animal RBCs displaying distinct cellular features. To close this knowledge gap, we probed chicken, horse, camel, and human fetal RBCs and compared data with human adults serving as a repository for future studies. Additionally, we assessed how measurements are affected under physiological conditions (species-specific temperature in autologous plasma vs. 25 °C in aqueous NaCl solution). In all RBC types, Ea decreased with increasing temperature irrespective of the suspension medium. In mammalian RBCs, adhesion increased with elevated temperatures and scaled with reported membrane sialic acid concentrations. In chicken only adhesion decreased with higher temperature, which we attribute to the lower AE-1 concentration allowing more membrane undulations. Ea decreased further in plasma at every test temperature, and adhesion was completely abolished, pointing to functional cell enlargement by adsorption of plasma components. This halo elevated RBC size by several hundreds of nanometers, blunted the thermal input, and will affect the coupling of RBCs with the flowing plasma. The study evidences the presence of a RBC surface layer and discusses the tremendous effects when RBCs are probed at physiological conditions.

Down syndrome (DS) is mostly caused by a trisomy of the entire Chromosome 21 (Trisomy 21, T21). Here, we use SWATH mass spectrometry to quantify protein abundance and protein turnover in fibroblasts from a monozygotic twin pair discordant for T21, and to profile protein expression in 11 unrelated DS individuals and matched controls. The integration of the steady-state and turnover proteomic data indicates that protein-specific degradation of members of stoichiometric complexes is a major determinant of T21 gene dosage outcome, both within and between individuals. This effect is not apparent from genomic and transcriptomic data. The data also reveal that T21 results in extensive proteome remodeling, affecting proteins encoded by all chromosomes. Finally, we find broad, organelle-specific post-transcriptional effects such as significant downregulation of the mitochondrial proteome contributing to T21 hallmarks. Overall, we provide a valuable proteomic resource to understand the origin of DS phenotypic manifestations. Trisomy 21 (T21) is a major cause of Down syndrome but little is known about its impact on the cellular proteome. Here, the authors define the proteome of T21 fibroblasts and its turnover and also map proteomic differences in monozygotic T21-discordant twins, revealing extensive, organelle-specific changes caused by T21.

Background and aims Soil organic phosphorus (P org ) is of interest for plant nutrition because it can comprise between 20 and 80% of total soil phosphate (P). This study aims to examine the effect of compost application on soil phosphatases and microbial biomass, which influence the P turnover and, furthermore, to examine the speciation of P org . Methods Soil from a long-term field experiment (since 1997) which compares compost application with inorganic fertilization was analyzed for calcium-acetate-lactate extractable P (CAL-P), Olsen-P, acid (Acid-P ase ) and alkaline (Alk-P ase ) phosphatase activity and microbial biomass P. P org speciation was additionally analyzed with liquid-state 31 P nuclear magnetic resonance spectroscopy ( 31 P-NMR). Results We found a significant increasing long-term effect of high compost application (equivalent to 400 kg ha −1 N (400)) on Acid-P ase (45%) and Alk-P ase (58%). After compost application, Acid-P ase increased by 41% in treatment 400 (3 days after compost application (DAA)). The 31 P-NMR analysis showed a significant increase of inorganic orthophosphate (55%) after high compost application. Furthermore, the total phosphomonoester region was significantly decreased in the treatment 400 (8%). Conclusions We demonstrated that long-term compost application increases phosphatase activity which plays a key role in the mineralization of soil P org . In particular, the decrease of the concentration of P org species in the phosphomonoester region in the treatment 400 with high compost application highlights that an increased turnover affects this soil P pool and may provide P to plants. This knowledge provides a better understanding of how the P cycle responds to long-term compost fertilization.

Adipose tissue expansion involves both differentiation of new precursors and size increase of mature adipocytes. While the two processes are well balanced in healthy tissues, obesity and diabetes type II are associated with abnormally enlarged adipocytes and excess lipid accumulation. Previous studies suggested a link between cell stiffness, volume and stem cell differentiation, although in the context of preadipocytes, there have been contradictory results regarding stiffness changes with differentiation. Thus, we set out to quantitatively monitor adipocyte shape and size changes with differentiation and lipid accumulation. We quantified by optical diffraction tomography that differentiating preadipocytes increased their volumes drastically. Atomic force microscopy (AFM)-indentation and -microrheology revealed that during the early phase of differentiation, human preadipocytes became more compliant and more fluid-like, concomitant with ROCK-mediated F-actin remodelling. Adipocytes that had accumulated large lipid droplets were more compliant, and further promoting lipid accumulation led to an even more compliant phenotype. In line with that, high fat diet-induced obesity was associated with more compliant adipose tissue compared to lean animals, both for drosophila fat bodies and murine gonadal adipose tissue. In contrast, adipose tissue of diabetic mice became significantly stiffer as shown not only by AFM but also magnetic resonance elastography. Altogether, we dissect relative contributions of the cytoskeleton and lipid droplets to cell and tissue mechanical changes across different functional states, such as differentiation, nutritional state and disease. Our work therefore sets the basis for future explorations on how tissue mechanical changes influence the behaviour of mechanosensitive tissue-resident cells in metabolic disorders.

Despite the essential role of nitrogen fertilizers in achieving high crop yields, current application practices often exhibit low efficiency. Optimizing nitrogen (N) fertilization in agriculture is, therefore, critical for enhancing crop productivity while ensuring sustainable food production. This study investigates the effects of nitrification inhibitors (Nis) such as Dimethyl Pyrazole Phosphate (DMPP) and Dimethyl Pyrazole Fulvic Acid (DMPFA), plant growth-promoting bacteria inoculation, and phosphorus (P) application on the soil-plant-microbe system in maize. DMPFA is an organic nitrification inhibitor that combines DMP and fulvic acid for the benefits of both compounds as a chelator. A comprehensive rhizobox experiment was conducted, employing varying levels of P, inoculant types, and Nis, to analyze the influence of these factors on various soil properties, maize fitness, and phenotypic traits, including root architecture and exudate profile. Additionally, the experiment examined the effects of treatments on the bacterial and fungal communities within the rhizosphere and maize roots. Our results showed that the use of Nis improved plant nutrition and biomass. For example, the use of DMPFA as a nitrification inhibitor significantly improved phosphorus use efficiency by up to 29%, increased P content to 37%, and raised P concentration in the shoot by 26%, compared to traditional ammonium treatments. The microbial communities inhabiting maize rhizosphere and roots were also highly influenced by the different treatments. Among them, the N treatment was the major driver in shaping bacterial and fungal communities in both plant compartments. Notably, Nis reduced significantly the abundance of bacterial groups involved in the nitrification process. Moreover, we observed that each experimental treatment employed in this investigation could select, promote, or reduce specific groups of beneficial or detrimental soil microorganisms. Overall, our results highlight the intricate interplay between soil amendments, microbial communities, and plant nutrient dynamics, suggesting that Nis, particularly DMPFA, could be pivotal in bolstering agricultural sustainability by optimizing nutrient utilization.