Sequential Enrichment Research Articles

Two-Step Enrichment Facilitates Background Reduction for Proteomic Analysis of Lysosomes.

Lysosomes constitute the main degradative compartment of most mammalian cells and are involved in various cellular functions. Most of them are catalyzed by lysosomal proteins, which typically are low abundant, complicating their analysis by mass spectrometry-based proteomics. To increase analytical performance and to enable profiling of lysosomal content, lysosomes are often enriched. Two approaches have gained popularity in recent years, namely, superparamagnetic iron oxide nanoparticles (SPIONs) and immunoprecipitation from cells overexpressing a 3xHA-tagged version of TMEM192 (TMEM-IP). The effect of these approaches on the lysosomal proteome has not been investigated to date. We addressed this topic through a combination of both techniques and proteomic analysis of lysosome-enriched fractions. For SPIONs treatment, we identified altered cellular iron homeostasis and moderate changes of the lysosomal proteome. For overexpression of TMEM192, we observed more pronounced effects in lysosomal protein expression, especially for lysosomal membrane proteins and those involved in protein trafficking. Furthermore, we established a combined strategy based on the sequential enrichment of lysosomes with SPIONs and TMEM-IP. This enabled increased purity of lysosome-enriched fractions and, through TMEM-IP-based lysosome enrichment from SPIONs flow-through and eluate fractions, additional insights into the properties of individual approaches. All data are available via ProteomeXchange with PXD048696.

TIMAHAC: Streamlined Tandem IMAC-HILIC Workflow for Simultaneous and High-Throughput Plant Phosphoproteomics and N-glycoproteomics

Protein post-translational modifications (PTMs) are crucial in plant cellular processes, particularly in protein folding and signal transduction. N-glycosylation and phosphorylation are notably significant PTMs, playing essential roles in regulating plant responses to environmental stimuli. However, current sequential enrichment methods for simultaneous analysis of phosphoproteome and N-glycoproteome are labor-intensive and time-consuming, limiting their throughput. Addressing this challenge, this study introduces a novel tandem S-Trap-IMAC-HILIC (S-Trap: suspension trapping; IMAC: immobilized metal ion affinity chromatography; HILIC: hydrophilic interaction chromatography) strategy, termed TIMAHAC, for simultaneous analysis of plant phosphoproteomics and N-glycoproteomics. This approach integrates IMAC and HILIC into a tandem tip format, streamlining the enrichment process of phosphopeptides and N-glycopeptides. The key innovation lies in the use of a unified buffer system and an optimized enrichment sequence to enhance efficiency and reproducibility. The applicability of TIMAHAC was demonstrated by analyzing the Arabidopsis phosphoproteome and N-glycoproteome in response to abscisic acid (ABA) treatment. Up to 1954 N-glycopeptides and 11,255 phosphopeptides were identified from Arabidopsis, indicating its scalability for plant tissues. Notably, distinct perturbation patterns were observed in the phosphoproteome and N-glycoproteome, suggesting their unique contributions to ABA response. Our results reveal that TIMAHAC offers a comprehensive approach to studying complex regulatory mechanisms and PTM interplay in plant biology, paving the way for in-depth investigations into plant signaling networks.

Systematic Optimization of Automated Phosphopeptide Enrichment for High-Sensitivity Phosphoproteomics

Improving coverage, robustness, and sensitivity is crucial for routine phosphoproteomics analysis by single-shot liquid chromatography-tandem mass spectrometry (LC-MS/MS) from minimal peptide inputs. Here, we systematically optimized key experimental parameters for automated on-bead phosphoproteomics sample preparation with a focus on low-input samples. Assessing the number of identified phosphopeptides, enrichment efficiency, site localization scores, and relative enrichment of multiply-phosphorylated peptides pinpointed critical variables influencing the resulting phosphoproteome. Optimizing glycolic acid concentration in the loading buffer, percentage of ammonium hydroxide in the elution buffer, peptide-to-beads ratio, binding time, sample, and loading buffer volumes allowed us to confidently identify >16,000 phosphopeptides in half-an-hour LC-MS/MS on an Orbitrap Exploris 480 using 30 μg of peptides as starting material. Furthermore, we evaluated how sequential enrichment can boost phosphoproteome coverage and showed that pooling fractions into a single LC-MS/MS analysis increased the depth. We also present an alternative phosphopeptide enrichment strategy based on stepwise addition of beads thereby boosting phosphoproteome coverage by 20%. Finally, we applied our optimized strategy to evaluate phosphoproteome depth with the Orbitrap Astral MS using a cell dilution series and were able to identify >32,000 phosphopeptides from 0.5 million HeLa cells in half-an-hour LC-MS/MS using narrow-window data-independent acquisition (nDIA).

Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities

Bayesian active learning methods have emerged for structural reliability analysis, showcasing more attractive features compared to existing active learning methods. The parallel adaptive Bayesian quadrature (PABQ) method, as a representative of them, allows to efficiently assessing small failure probabilities but faces the problem of empirically specifying several important parameters. The unreasonable parameter settings could lead to the inaccurate estimates of failure probability or the non-convergence of active learning. This study proposes a refined PABQ (R-PABQ) method by presenting three novel refinements to overcome the drawbacks of PABQ. Firstly, a sequential population enrichment strategy is presented and embedded into the importance ball sampling technique to solve the computer memory problem when involving large sample population. Secondly, an adaptive determination strategy for radius is developed to automatically adjust the sampling region during the active learning procedure. Lastly, an adaptive multi-point selection method is proposed to identify a batch of points to enable parallel computing. The effectiveness of the proposed R-PABQ method is demonstrated by four numerical examples. Results show that the proposed method can estimate small failure probabilities (e.g., 10−7∼10−9) with superior accuracy and efficiency over several existing active learning reliability methods.

A Tip-Based Workflow for Sensitive IMAC-Based Low Nanogram Level Phosphoproteomics.

Analyzing the phosphoproteome at nanoscale poses a significant challenge, mainly due to the substantial sample loss from nonspecific surface adsorption during the enrichment of low stoichiometric phosphopeptides. Here, we describe a tandem tip-based phosphoproteomics sample preparation method capable of sequential sample cleanup and enrichment without the need for additional sample transfer, thereby minimizing sample loss. Integration of this method to our recently developed SOP (surfactant-assisted one-pot sample preparation) and iBASIL (improved boosting to amplify signal with isobaric labeling) approaches creates a streamlined workflow, enabling sensitive, high-throughput nanoscale phosphoproteomics measurements.

A study on speciation and enrichment of rare earth elements (REE) by sequential extraction from a potential coal fly ash resource and its role in REE extractability

Coal fly ash (CFA) is a potential secondary Rare Earth Element (REE) source that needs an efficient enrichment and extraction process. Annually, coal-fired power plants generate nearly 1 billion tonnes of coal ash. India alone produced 270.82 million tonnes of CFA in 2021–22. The average global concentration of REE in coal ash is 403.5 mg/kg. The present authors have already studied some promising CFAs from Indian thermal power stations and one such CFA is used in the present study for the sequential extraction (SE), speciation, and enrichment of REEs. Organic acids are used for SE to determine different fractions of REEs and it is found that REEs are mostly associated with amorphous Mn-oxide and organic and sulfide fractions. About 84% of REEs are in the glassy phase that SE cannot dissolve. The main components of CFA and SE residues are quartz, mullite, and glassy phase (52.0–59.2%). The XRF analysis showed that CFA is ‘Class F' (ASTM C618–19). The ESEM – EDS and backscatter imaging revealed monazite-(La) mineral as the REE carrier in CFA. Furthermore, enrichment studies using acid and alkali media have been performed. Alkali treatment with NaOH and KOH increased total REE by 1.61 and 1.32 times, respectively. Acidic treatment with HCl and oxalic acid increased total REE by 1.27 and 1.09 times, respectively. Therefore, NaOH followed by HCl treatment could be a cost-effective and sustainable REE enrichment and extraction method from CFA.

Maximal performance of intact N-glycopeptide enrichment using sequential HILIC and MAX columns.

Low abundance and heterogeneity of N-glycosylation at the peptide level poses a great challenge to the structural and functional analysis of glycosylation in the field of glycobiology. Solving this conundrum requires a sufficient and specific method for intact N-glycopeptide enrichment. Using the C18 or HLB desalting column followed by the mixed-mode strong anion exchange (MAX) or hydrophilic interaction chromatography (HILIC) glycopeptide enrichment column are commonly applied approaches for sample preparation of intact N-glycopeptides from complex samples. Herein, we compared the effects of different combinations of two desalting columns and two enrichment columns using equal amounts of mouse brain tissues from the same source. The results revealed the C18 column was a bit superior to the HLB column, and the MAX and HILIC columns were complementary on intact N-glycopeptides enrichment. Additionally, the results also demonstrated that enriching glycopeptides using a HILIC column followed by a MAX column from the flow-through solution got a better enrichment performance than the reversed order. Based on these results, the sequential enrichment of glycopeptides using HILIC and then MAX columns could maximize the enrichment performance of intact N-glycopeptides, and therefore is an option for in-depth analysis of site-specific glycoproteome.

Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited set of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a readout of aberrant signaling and has the potential to identify new targets and guide treatment decisions. Using two-step sequential phosphopeptide enrichment, we generate a comprehensive phosphoproteome and proteome of nine PDAC cell lines, encompassing more than 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases. By using integrative inferred kinase activity (INKA) scoring, we identify multiple (parallel) activated kinases that are subsequently matched to kinase inhibitors. Compared with high-dose single-drug treatments, INKA-tailored low-dose 3-drug combinations against multiple targets demonstrate superior efficacy against PDAC cell lines, organoid cultures, and patient-derived xenografts. Overall, this approach is particularly more effective against the aggressive mesenchymal PDAC model compared with the epithelial model in both preclinical settings and may contribute to improved treatment outcomes in PDAC patients.

Simultaneous Profiling of Palmitoylomics and Glycomics with Photo/pH Dual-Responsive Magnetic Nanocomposites.

Following an in-depth examination of a single type of protein posttranslational modification, the synergistic analysis of two or more modification types has gradually emerged as a focal point in proteomic research. Palmitoylation and glycosylation are both critical for protein, implicated in carcinogenesis and inflammation. In this study, novel dual-responsive magnetic nanocomposites that serve as an ideal platform for the sequential or simultaneous enrichment of palmitoyl and glycopeptides are reported. The nanocomposites denoted as magDVS-VBA are constructed by modifying magnetic nanoparticles with azobenzene and divinyl sulfone (DVS), and self-assembled with 4-vinylbenzeneboronic acid (VBA)-immobilized β-cyclodextrin, which responds to light. The incorporated DVS component possesses the ability to recognize palmitoyl or glycopeptides under different pH conditions, whereas the introduction of VBA enhances the affinity of the nanocomposite for glycopeptides. Notably, magDVS-VBA exhibits flexible photo-, pH-, and magnetic-responsive capabilities, enabling the simultaneous recognition of hydrophobic palmitoyl peptides and hydrophilic glycopeptides for the first time. The developed platform demonstrates high specificity for sensitive palmitoylomics and glycomics analysis of mouse liver tissue, providing an effective method for studying of their crosstalk, and potential implications in clinical applications.

Development of plastic-degrading microbial consortia by induced selection in microcosms.

The increase in the production of highly recalcitrant plastic materials, and their accumulation in ecosystems, generates the need to investigate new sustainable strategies to reduce this type of pollution. Based on recent works, the use of microbial consortia could contribute to improving plastic biodegradation performance. This work deals with the selection and characterization of plastic-degrading microbial consortia using a sequential and induced enrichment technique from artificially contaminated microcosms. The microcosm consisted of a soil sample in which LLDPE (linear low-density polyethylene) was buried. Consortia were obtained from the initial sample by sequential enrichment in a culture medium with LLDPE-type plastic material (in film or powder format) as the sole carbon source. Enrichment cultures were incubated for 105 days with monthly transfer to fresh medium. The abundance and diversity of total bacteria and fungi were monitored. Like LLDPE, lignin is a very complex polymer, so its biodegradation is closely linked to that of some recalcitrant plastics. For this reason, counting of ligninolytic microorganisms from the different enrichments was also performed. Additionally, the consortium members were isolated, molecularly identified and enzymatically characterized. The results revealed a loss of microbial diversity at each culture transfer at the end of the induced selection process. The consortium selected from selective enrichment in cultures with LLDPE in powder form was more effective compared to the consortium selected in cultures with LLDPE in film form, resulting in a reduction of microplastic weight between 2.5 and 5.5%. Some members of the consortia showed a wide range of enzymatic activities related to the degradation of recalcitrant plastic polymers, with Pseudomonas aeruginosa REBP5 or Pseudomonas alloputida REBP7 strains standing out. The strains identified as Castellaniella denitrificans REBF6 and Debaryomyces hansenii RELF8 were also considered relevant members of the consortia although they showed more discrete enzymatic profiles. Other consortium members could collaborate in the prior degradation of additives accompanying the LLDPE polymer, facilitating the subsequent access of other real degraders of the plastic structure. Although preliminary, the microbial consortia selected in this work contribute to the current knowledge of the degradation of recalcitrant plastics of anthropogenic origin accumulated in natural environments.

Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy.

Comparative analysis of EpCAM high-expressing and low-expressing circulating tumour cells with regard to their clonal relationship and clinical value

BackgroundCirculating tumour cells (CTCs) are mainly enriched based on the epithelial cell adhesion molecule (EpCAM). Although it was shown that an EpCAM low-expressing CTC fraction is not captured by such approaches, knowledge about its prognostic and predictive relevance and its relation to EpCAM-positive CTCs is lacking.MethodsWe developed an immunomagnetic assay to enrich CTCs from metastatic breast cancer patients EpCAM independently using antibodies against Trop-2 and CD-49f and characterised their EpCAM expression. DNA of single EpCAM high expressing and low expressing CTCs was analyzed regarding chromosomal aberrations and predictive mutations. Additionally, we compared CTC-enrichment on the CellSearch system using this antibody mix and the EpCAM based enrichment.ResultsBoth antibodies acted synergistically in capturing CTCs. Patients with EpCAM high-expressing CTCs had a worse overall and progression-free survival. EpCAM high- and low-expressing CTCs presented similar chromosomal aberrations and mutations indicating a close evolutionary relationship. A sequential enrichment of CTCs from the EpCAM-depleted fraction yielded a population of CTCs not captured EpCAM dependently but harbouring predictive information.ConclusionsOur data indicate that EpCAM low-expressing CTCs could be used as a valuable tumour surrogate material—although they may be prognostically less relevant than EpCAM high-expressing CTCs—and have particular benefit if no CTCs are detected using EpCAM-dependent technologies.

Determination of Vanadium(IV) and Vanadium(V) in Beverages by Two-Step Direct Immersion Single-Drop Microextraction with Graphite Furnace Atomic Absorption Spectrometry (GFAAS)

A novel two-step direct immersion single-drop microextraction (TS-DI-SDME) was reported for the sequential separation and enrichment of V(V) and V(IV) followed by graphite furnace atomic absorption spectrometry detection. Theonyltrifluoroacetone (HTTA) and chloroform were used as the chelating reagent and extraction solvent for TS-DI-SDME. In the first step, V(V)-HTTA complexes were separated and enriched in one organic solvent drop at pH 2.5, while V(IV) remained in the solution. Next, another organic solvent drop containing HTTA was immersed in the original solution after the extraction of V(V) for the enrichment of V(IV) at pH 4.5. This procedure avoids tedious and complicated pre-oxidation/pre-reduction operations, which may cause contamination and error. Under the optimized conditions, the limits of detection were equal to 3.1 and 2.6 ng L−1 for V(IV) and V(V) with relative standard deviation values of 4.9 and 5.8%, respectively. An enrichment factor of 300-fold was achieved for V(IV) and V(V). This method was successfully utilized for the determination of V(IV) and V(V) in beverages. To validate this approach, a water-certified reference material was analyzed with satisfactory results.

Determination of Tl(III) and Tl(I) in food samples with two-step direct immersion single-drop microextraction followed by graphite furnace atomic absorption spectrometry

In this study, a new procedure of two-step direct immersion single-drop microextraction (TS-DI-SDME) was firstly developed for the sequential separation and enrichment of Tl(III) and Tl(I) before graphite furnace atomic absorption spectrometry detection. At pH 6.0, Tl(III) selectively reacts with 1-(2-Pyridylazo)− 2-naphthol to form the complexes which can be extracted into one organic drop, while Tl(I) remained in the solution. Then, another organic drop containing dicyclohexano-18-crown-6 was immersed in the sample solution after the extraction of Tl(III) for the enrichment of Tl(I) at the same pH value. Main parameters affecting the separation and enrichment of Tl species were investigated. Under optimized conditions, limits of quantification (LODs) were 6.3 ng L−1 and 8.3 ng L−1 for Tl(III) and Tl(I), respectively. Repeatability and reproducibility were assessed by calculating relative standard deviations (RSDs), which were less than 5.1% and 6.7% for Tl(III) and Tl(I), respectively. Preconcentration factors of 300-fold were achieved for Tl species. This method was used successfully for the determination of Tl(III) and Tl(I) in food samples. To validate this procedure, a certified reference material of milk powder was analyzed with the satisfactory results. This method may avoid the problems of tedious operations, sample contamination and analysis errors in redox speciation strategies.

Solidified floating organic drop microextraction in tandem with syringe membrane miro-solid phase extraction for sequential detection of thallium (III) and thallium (I) by graphite furnace atomic absorption spectrometry

In the present study, a novel method based on solidified floating organic drop microextraction (SFODME) combined with syringe membrane micro-solid phase extraction (SMMSPE) was proposed for the sequential separation and enrichment of Tl(III) and Tl(I) followed by graphite furnace atomic absorption spectrometry detection. In SFODME, Tl(III) can react with 1-(2-Pyridylazo)-2-naphthol at pH 8.0 to form the complexes which can be extracted into an organic drop, while Tl(I) was remained in the solution. In SMMSPE, flexible TiO2@SiO2 nanofiber membrane was used as the sorbent for the enrichment of Tl(I) in the sample solution after the separation of Tl(III). This method did not require tedious pre-oxidation/pre-reduction operation and time-consuming centrifugation/filtration steps, which may cause sample contamination and analysis errors. Main parameters influencing the separation and enrichment of the target species were studied. Under the selected conditions, the detection limits for this method were 1.7 and 2.6 ng/L for Tl(III) and Tl(I) with relative standard deviations of 6.1 % and 5.2 %, respectively. This method was successfully used for the determination of the target species in environmental water samples and two certified reference materials. The determined values were in good agreement with the certified values.

SeEn: Sequential enriched datasets for sequence-aware recommendations

The recommendation of items based on the sequential past users’ preferences has evolved in the last few years, mostly due to deep learning approaches, such as BERT4Rec. However, in scientific fields, recommender systems for recommending the next best item are not widely used. The main goal of this work is to improve the results for the recommendation of the next best item in scientific domains using sequence aware datasets and algorithms. In the first part of this work, we present the adaptation of a previous method (LIBRETTI) for creating sequential recommendation datasets for scientific fields. The results were assessed in Astronomy and Chemistry. In the second part of this work, we propose a new approach to improve the datasets, not the algorithms, to obtain better recommendations. The new hybrid approach is called sequential enrichment (SeEn), which consists of adding to a sequence of items the n most similar items after each original item. The results show that the enriched sequences obtained better results than the original ones. The Chemistry dataset improved by approximately seven percentage points and the Astronomy dataset by 16 percentage points for Hit Ratio and Normalized Discounted Cumulative Gain.

Ontogenetic rules for the molecular diversification of hypothalamic neurons.

The hypothalamus is an evolutionarily conserved endocrine interface that, among other roles, links central homeostatic control to adaptive bodily responses by releasing hormones and neuropeptides from its many neuronal subtypes. In its preoptic, anterior, tuberal and mammillary subdivisions, a kaleidoscope of magnocellular and parvocellular neuroendocrine command neurons, local-circuit neurons, and neurons that project to extrahypothalamic areas are intermingled in partially overlapping patches of nuclei. Molecular fingerprinting has produced data of unprecedented mass and depth to distinguish and even to predict the synaptic and endocrine competences, connectivity and stimulus selectivity of many neuronal modalities. These new insights support eminent studies from the past century but challenge others on the molecular rules that shape the developmental segregation of hypothalamic neuronal subtypes and their use of morphogenic cues for terminal differentiation. Here, we integrate single-cell RNA sequencing studies with those of mouse genetics and endocrinology to describe key stages of hypothalamus development, including local neurogenesis, the direct terminal differentiation of glutamatergic neurons, transition cascades for GABAergic and GABAergic cell-derived dopamine cells, waves of local neuronal migration, and sequential enrichment in neuropeptides and hormones. We particularly emphasize how transcription factors determine neuronal identity and, consequently, circuit architecture, and whether their deviations triggered by environmental factors and hormones provoke neuroendocrine illnesses.

Acidogenic fermentation of food waste in a leachate bed reactor (LBR) at high volumetric organic Loading: Effect of granular activated carbon (GAC) and sequential enrichment of inoculum

This study investigated the impact of different granular activated carbon (GAC) loadings and inoculum enrichment on acidogenic fermentation of food waste in a leachate bed reactor (LBR) operated at a high volumetric organic loading of 49 g VS/Lreactor. LBR with a high GAC loading of 0.51 g GAC/g VSfood waste achieved hydrolysis yield of 620 g SCOD/kg VSadded, significantly (P ≤ 0.05) higher to that obtained for LBRs with low or no GAC loading. A high GAC loading also resulted in a higher acidification yield of 507 g CODSCFA/kg VSadded. Butyrate dominated the short-chain fatty acid (SCFA) composition by constituting 57–60 % of total SCFA at high GAC loadings, while the composition of acetate (38–40 %) and butyrate (36–38 %) were similar at lower GAC loadings. Inoculum enrichment further improved the hydrolysis and acidogenesis yields by 10–22 % resulting in the final hydrolysis yield of 683 g SCOD/kg VSadded and acidification yield of 617 g CODSCFA/kg VSadded.

Phosphoproteome profiling of hippocampal synaptic plasticity

The balance between the actions of protein kinases and phosphatases is crucial for neuronal functions, including synaptic plasticity. Although the phosphorylation and dephosphorylation of neuronal proteins are regulated by synaptic plasticity, no systematic analyses of this have yet been conducted. We performed a phosphoproteomic analysis of hippocampal synaptic plasticity using a nano-Acquity/Synapt LC-MS/MS system. Neuronal proteins were extracted from hippocampal tissues and cultured neurons exposed to long-term potentiation (LTP) or long-term depression (LTD). Filter-aided sample preparation (FASP) was performed to remove residual anionic detergents for complete tryptic digestion. Phosphopeptides were then enriched using TiO2 chromatography, followed by immunoaffinity chromatography with an anti-phosphotyrosine antibody. Among the 1500 phosphopeptides identified by LC-MS/MS, 374 phosphopeptides were detected simultaneously in both hippocampal tissues and cultured neurons. Semi-quantification counting the number of spectra of each phosphopeptide showed that 42 of 374 phosphopeptides changed significantly depending on synaptic plasticity. In conclusion, a new proteomic method using sequential enrichment of phosphopeptides and semi-quantification enabled the phosphoproteomic analysis of hippocampal synaptic plasticity.

A Dual Enrichment Strategy Provides Soil- and Digestate-Competent Nitrous Oxide-Respiring Bacteria for Mitigating Climate Forcing in Agriculture.

ABSTRACTManipulating soil metabolism through heavy inoculation with microbes is feasible if organic wastes can be utilized as the substrate for growth and vector as a fertilizer. This, however, requires organisms active in both digestate and soil (generalists). Here, we present a dual enrichment strategy to enrich and isolate such generalists among N2O-respiring bacteria (NRB) in soil and digestates, to be used as an inoculum for strengthening the N2O-reduction capacity of soils. The enrichment strategy utilizes sequential batch enrichment cultures alternating between sterilized digestate and soil as substrates, with each batch initiated with limited O2 and unlimited N2O. The cultures were monitored for gas kinetics and community composition. As predicted by a Lotka-Volterra competition model, cluster analysis identified generalist operational taxonomic units (OTUs) which became dominant, digestate/soil-specialists which did not, and a majority that were gradually diluted out. We isolated several NRBs circumscribed by generalist OTUs. Their denitrification genes and phenotypes predicted a variable capacity to act as N2O-sinks, while all genomes predicted broad catabolic capacity. The latter contrasts with previous attempts to enrich NRB by anaerobic incubation of unsterilized digestate only, which selected for organisms with a catabolic capacity limited to fermentation products. The two isolates with the most promising characteristics as N2O sinks were a Pseudomonas sp. with a full-fledged denitrification-pathway and a Cloacibacterium sp. carrying only N2O reductase (clade II), and soil experiments confirmed their capacity to reduce N2O-emissions from soil. The successful enrichment of NRB with broad catabolic spectra suggests that the concept of dual enrichment should also be applicable for enrichment of generalists with traits other than N2O reduction.