Efficacy and safety of nanoparticle albumin-bound paclitaxel in taxane-pretreated metastatic breast cancer patients.

BACKGROUND: Taxanes are the basic components of breast cancer chemotherapy. Nanoparticle albumin-bound paclitaxel (nab-paclitaxel) shows improved antitumor effects because of more targeted delivery. However, the effects of nab-paclitaxel have not been systematically studied in patients with metastatic breast cancer (MBC) pretreated with taxanes. Considering the limited treatment options for MBC, this study retrospectively evaluated the clinical efficacy and adverse effects of nab-paclitaxel in patients with taxane-pretreated MBC. METHODS: Patients who had previously received taxanes and subsequently received nab-paclitaxel chemotherapy for MBC at Jiangsu Cancer Hospital between October 2014 and April 2022 were included for analysis. The primary end point was progression-free survival (PFS), and the secondary end points were the objective response rate (ORR), disease control rate (DCR), clinical benefit rate (CBR), and side effects. RESULTS: A total of 236 female patients with MBC were included. The median PFS was 7.20 months (95% confidence interval [CI], 6.63-7.80 months), and the ORR, DCR, and CBR were 29.55% (95% CI, 23.50%-35.60%), 83.64% (95% CI, 78.70%-88.60%), and 56.36% (95% CI, 49.80%-63.00%), respectively. Following nab-paclitaxel treatment, the median PFS of patients who were sensitive to taxanes during previous treatments was significantly longer than that of patients who were resistant to taxanes (7.57 months vs. 4.43 months, p < .001). The most common adverse events were sensory neuropathy (89.83%), neutropenia (48.73%), leukopenia (46.61%), and anemia (35.59%). CONCLUSION: Nab-paclitaxel demonstrated clinical activity in taxane-pretreated patients with MBC. This beneficial effect was observed both in patients who were sensitive and resistant to taxanes during previous treatments. These results suggest nab-paclitaxel as the preferred chemotherapy regimen in patients with MBC, regardless of their sensitivity to taxanes during previous treatments.

Active anaerobic methane oxidation and sulfur disproportionation in the deep terrestrial subsurface.

Microbial life is widespread in the terrestrial subsurface and present down to several kilometers depth, but the energy sources that fuel metabolism in deep oligotrophic and anoxic environments remain unclear. In the deep crystalline bedrock of the Fennoscandian Shield at Olkiluoto, Finland, opposing gradients of abiotic methane and ancient seawater-derived sulfate create a terrestrial sulfate-methane transition zone (SMTZ). We used chemical and isotopic data coupled to genome-resolved metaproteogenomics to demonstrate active life and, for the first time, provide direct evidence of active anaerobic oxidation of methane (AOM) in a deep terrestrial bedrock. Proteins from Methanoperedens (formerly ANME-2d) are readily identifiable despite the low abundance (≤1%) of this genus and confirm the occurrence of AOM. This finding is supported by 13C-depleted dissolved inorganic carbon. Proteins from Desulfocapsaceae and Desulfurivibrionaceae, in addition to 34S-enriched sulfate, suggest that these organisms use inorganic sulfur compounds as both electron donor and acceptor. Zerovalent sulfur in the groundwater may derive from abiotic rock interactions, or from a non-obligate syntrophy with Methanoperedens, potentially linking methane and sulfur cycles in Olkiluoto groundwater. Finally, putative episymbionts from the candidate phyla radiation (CPR) and DPANN archaea represented a significant diversity in the groundwater (26/84 genomes) with roles in sulfur and carbon cycling. Our results highlight AOM and sulfur disproportionation as active metabolisms and show that methane and sulfur fuel microbial activity in the deep terrestrial subsurface.

Comparison of allergen quantification strategies for egg, milk, and peanut in food using targeted LC-MS/MS.

Methods for the detection and quantification of food allergens in complex matrices are necessary to ensure compliance with labeling regulations and assess the effectiveness of food allergen preventive controls. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as an orthogonal technique in complement to immunochemical-based assays. However, the absence of established guidelines for MS-based quantification of allergens in food has limited harmonization among the method development community. In this study, different quantification strategies were evaluated using a previously developed multiplexed LC-MS/MS method for the detection of egg, milk, and peanut. Peptide performance criteria (retention time, signal-to-noise ratio, and ion ratio tolerance) were established and quantification approaches using varying calibrants, internal standards, background matrices, and calibration curve preparation schemes were systematically evaluated to refine the previous method for routine laboratory use. A matrix-matched calibration curve using allergen ingredients as calibrants and stable isotope-labeled peptides as internal standards provided the most accurate quantitative results. The strategy was further verified with commercially available reference materials and allowed for the confident detection and quantification of food allergens. This work highlights the need for transparency in calibration strategy and peptide performance requirements for effective evaluation of mass spectrometric methods for the quantification of food allergens.

A nitrogenase-like enzyme system catalyzes methionine, ethylene, and methane biogenesis.

Bacterial production of gaseous hydrocarbons such as ethylene and methane affects soil environments and atmospheric climate. We demonstrate that biogenic methane and ethylene from terrestrial and freshwater bacteria are directly produced by a previously unknown methionine biosynthesis pathway. This pathway, present in numerous species, uses a nitrogenase-like reductase that is distinct from known nitrogenases and nitrogenase-like reductases and specifically functions in C-S bond breakage to reduce ubiquitous and appreciable volatile organic sulfur compounds such as dimethyl sulfide and (2-methylthio)ethanol. Liberated methanethiol serves as the immediate precursor to methionine, while ethylene or methane is released into the environment. Anaerobic ethylene production by this pathway apparently explains the long-standing observation of ethylene accumulation in oxygen-depleted soils. Methane production reveals an additional bacterial pathway distinct from archaeal methanogenesis.

Smart Soft Sensor Design with Hierarchical Sampling Strategy of Ensemble Gaussian Process Regression for Fermentation Processes.

Accurate and real-time quality prediction to realize the optimal process control at a competitive price is an important issue in Industrial 4.0. This paper shows a successful engineering application of how smart soft sensors can be combined with machine learning technique to significantly save human resources and improve performance under complex industrial conditions. Ensemble learning based soft sensors succeed in capturing complex nonlinearities, frequent dynamic changes, as well as time-varying characteristics in industrial processes. However, local model regions under traditional ensemble modelling methods are highly dependent on labeled data samples and, hence, their prediction accuracy might get affected when labeled samples are limited. A novel active learning (AL) framework upon the ensemble Gaussian process regression (GPR) model is proposed for smart soft sensor design in order to overcome this drawback. Firstly, to iteratively select the most informative unlabeled samples for labeling with hierarchical sampling based AL strategy, to then apply Gaussian mixture model (GMM) technique to autonomously identify operation phases, to further construct local GPR models without human involvement, and finally to integrate the base predictors by applying the Bayesian fusion strategy. Comparative studies for the penicillin fermentation process demonstrate the reliability and superiority of the recommended smart soft sensing. The cost of human annotation can be dramatically reduced by at least half while the prediction performance simultaneously keeps high.

Active sulfur cycling in the terrestrial deep subsurface.

The deep terrestrial subsurface remains an environment where there is limited understanding of the extant microbial metabolisms. At Olkiluoto, Finland, a deep geological repository is under construction for the final storage of spent nuclear fuel. It is therefore critical to evaluate the potential impact microbial metabolism, including sulfide generation, could have upon the safety of the repository. We investigated a deep groundwater where sulfate is present, but groundwater geochemistry suggests limited microbial sulfate-reducing activity. Examination of the microbial community at the genome-level revealed microorganisms with the metabolic capacity for both oxidative and reductive sulfur transformations. Deltaproteobacteria are shown to have the genetic capacity for sulfate reduction and possibly sulfur disproportionation, while Rhizobiaceae, Rhodocyclaceae, Sideroxydans, and Sulfurimonas oxidize reduced sulfur compounds. Further examination of the proteome confirmed an active sulfur cycle, serving for microbial energy generation and growth. Our results reveal that this sulfide-poor groundwater harbors an active microbial community of sulfate-reducing and sulfide-oxidizing bacteria, together mediating a sulfur cycle that remained undetected by geochemical monitoring alone. The ability of sulfide-oxidizing bacteria to limit the accumulation of sulfide was further demonstrated in groundwater incubations and highlights a potential sink for sulfide that could be beneficial for geological repository safety.

Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases.

Background: To effectively safeguard the food-allergic population and support compliance with food-labeling regulations, the food industry and regulatory agencies require reliable methods for food allergen detection and quantification. MS-based detection of food allergens relies on the systematic identification of robust and selective target peptide markers. The selection of proteotypic peptide markers, however, relies on the availability of high-quality protein sequence information, a bottleneck for the analysis of many plant-based proteomes. Method: In this work, data were compiled for reference tree nut ingredients and evaluated using a parsimony-driven global proteomics workflow. Results: The utility of supplementing existing incomplete protein sequence databases with translated genomic sequencing data was evaluated for English walnut and provided enhanced selection of candidate peptide markers and differentiation between closely related species. Highlights: Future improvements of protein databases and release of genomics-derived sequences are expected to facilitate the development of robust and harmonized LC-tandem MS-based methods for food allergen detection.

Metaproteomics reveals persistent and phylum-redundant metabolic functional stability in adult human gut microbiomes of Crohn's remission patients despite temporal variations in microbial taxa, genomes, and proteomes.

BACKGROUND: The gut microbiome plays a fundamental role in the human host's overall health by contributing key biological functions such as expanded metabolism and pathogen defense/immune control. In a healthy individual, the gut microbiome co-exists within the human host in a symbiotic, non-inflammatory relationship that enables mutual benefits, such as microbial degradation of indigestible food products into small molecules that the host can utilize, and enhanced pathogen defense. In abnormal conditions, such as Crohn's disease, this favorable metabolic relationship breaks down and a variety of undesirable activities result, including chronic inflammation and other health-related issues. It has been difficult, however, to elucidate the overall functional characteristics of this relationship because the microbiota can vary substantially in composition for healthy humans and possibly even more in individuals with gut disease conditions such as Crohn's disease. Overall, this suggests that microbial membership composition may not be the best way to characterize a phenotype. Alternatively, it seems to be more informative to examine and characterize the functional composition of a gut microbiome. Towards that end, this study examines 25 metaproteomes measured in several Crohn's disease patients' post-resection surgery across the course of 1 year, in order to examine persistence of microbial taxa, genes, proteins, and metabolic functional distributions across time in individuals whose microbiome might be more variable due to the gut disease condition. RESULTS: The measured metaproteomes were highly personalized, with all the temporally-related metaproteomes clustering most closely by individual. In general, the metaproteomes were remarkably distinct between individuals and to a lesser extent within individuals. This prompted a need to characterize the metaproteome at a higher functional level, which was achieved by annotating identified protein groups with KEGG orthologous groups to infer metabolic modules. At this level, similar and redundant metabolic functions across multiple phyla were observed across time and between individuals. Tracking through these various metabolic modules revealed a clear path from carbohydrate, lipid, and amino acid degradation to central metabolism and finally the production of fermentation products. CONCLUSIONS: The human gut metaproteome can vary quite substantially across time and individuals. However, despite substantial intra-individual variation in the metaproteomes, there is a clear persistence of conserved metabolic functions across time and individuals. Additionally, the persistence of these core functions is redundant across multiple phyla but is not always observable in the same sample. Finally, the gut microbiome's metabolism is not driven by a set of discrete linear pathways but a web of interconnected reactions facilitated by a network of enzymes that connect multiple molecules across multiple pathways.

Biogeochemical Cycling by a Low-Diversity Microbial Community in Deep Groundwater.

Olkiluoto, an island on the south-west coast of Finland, will host a deep geological repository for the storage of spent nuclear fuel. Microbially induced corrosion from the generation of sulphide is therefore a concern as it could potentially compromise the longevity of the copper waste canisters. Groundwater at Olkiluoto is geochemically stratified with depth and elevated concentrations of sulphide are observed when sulphate-rich and methane-rich groundwaters mix. Particularly high sulphide is observed in methane-rich groundwater from a fracture at 530.6 mbsl, where mixing with sulphate-rich groundwater occurred as the result of an open drill hole connecting two different fractures at different depths. To determine the electron donors fuelling sulphidogenesis, we combined geochemical, isotopic, metagenomic and metaproteomic analyses. This revealed a low diversity microbial community fuelled by hydrogen and organic carbon. Sulphur and carbon isotopes of sulphate and dissolved inorganic carbon, respectively, confirmed that sulphate reduction was ongoing and that CO2 came from the degradation of organic matter. The results demonstrate the impact of introducing sulphate to a methane-rich groundwater with limited electron acceptors and provide insight into extant metabolisms in the terrestrial subsurface.

Hospitalized Premature Infants Are Colonized by Related Bacterial Strains with Distinct Proteomic Profiles.

During the first weeks of life, microbial colonization of the gut impacts human immune system maturation and other developmental processes. In premature infants, aberrant colonization has been implicated in the onset of necrotizing enterocolitis (NEC), a life-threatening intestinal disease. To study the premature infant gut colonization process, genome-resolved metagenomics was conducted on 343 fecal samples collected during the first 3 months of life from 35 premature infants housed in a neonatal intensive care unit, 14 of whom developed NEC, and metaproteomic measurements were made on 87 samples. Microbial community composition and proteomic profiles remained relatively stable on the time scale of a week, but the proteome was more variable. Although genetically similar organisms colonized many infants, most infants were colonized by distinct strains with metabolic profiles that could be distinguished using metaproteomics. Microbiome composition correlated with infant, antibiotics administration, and NEC diagnosis. Communities were found to cluster into seven primary types, and community type switched within infants, sometimes multiple times. Interestingly, some communities sampled from the same infant at subsequent time points clustered with those of other infants. In some cases, switches preceded onset of NEC; however, no species or community type could account for NEC across the majority of infants. In addition to a correlation of protein abundances with organism replication rates, we found that organism proteomes correlated with overall community composition. Thus, this genome-resolved proteomics study demonstrated that the contributions of individual organisms to microbiome development depend on microbial community context.IMPORTANCE Humans are colonized by microbes at birth, a process that is important to health and development. However, much remains to be known about the fine-scale microbial dynamics that occur during the colonization period. We conducted a genome-resolved study of microbial community composition, replication rates, and proteomes during the first 3 months of life of both healthy and sick premature infants. Infants were found to be colonized by similar microbes, but each underwent a distinct colonization trajectory. Interestingly, related microbes colonizing different infants were found to have distinct proteomes, indicating that microbiome function is not only driven by which organisms are present, but also largely depends on microbial responses to the unique set of physiological conditions in the infant gut.

Insights into the Evolution of Host Association through the Isolation and Characterization of a Novel Human Periodontal Pathobiont, Desulfobulbus oralis.

The human oral microbiota encompasses representatives of many bacterial lineages that have not yet been cultured. Here we describe the isolation and characterization of previously uncultured Desulfobulbus oralis, the first human-associated representative of its genus. As mammalian-associated microbes rarely have free-living close relatives, D. oralis provides opportunities to study how bacteria adapt and evolve within a host. This sulfate-reducing deltaproteobacterium has adapted to the human oral subgingival niche by curtailing its physiological repertoire, losing some biosynthetic abilities and metabolic independence, and by dramatically reducing environmental sensing and signaling capabilities. The genes that enable free-living Desulfobulbus to synthesize the potent neurotoxin methylmercury were also lost by D. oralis, a notably positive outcome of host association. However, horizontal gene acquisitions from other members of the microbiota provided novel mechanisms of interaction with the human host, including toxins like leukotoxin and hemolysins. Proteomic and transcriptomic analysis revealed that most of those factors are actively expressed, including in the subgingival environment, and some are secreted. Similar to other known oral pathobionts, D. oralis can trigger a proinflammatory response in oral epithelial cells, suggesting a direct role in the development of periodontal disease.IMPORTANCE Animal-associated microbiota likely assembled as a result of numerous independent colonization events by free-living microbes followed by coevolution with their host and other microbes. Through specific adaptation to various body sites and physiological niches, microbes have a wide range of contributions, from beneficial to disease causing. Desulfobulbus oralis provides insights into genomic and physiological transformations associated with transition from an open environment to a host-dependent lifestyle and the emergence of pathogenicity. Through a multifaceted mechanism triggering a proinflammatory response, D. oralis is a novel periodontal pathobiont. Even though culture-independent approaches can provide insights into the potential role of the human microbiome "dark matter," cultivation and experimental characterization remain important to studying the roles of individual organisms in health and disease.

Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life.

BACKGROUND: Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. However, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota). RESULTS: We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants' gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for each of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. Applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production. CONCLUSIONS: Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.

Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota.

The human gastrointestinal tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome is not merely a collection of opportunistic parasites, but rather provides important functions to the host that are absolutely critical to many aspects of health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial metaproteomics provides the ability to characterize the human gut microbiota functions and metabolic activities at a remarkably deep level, revealing information about microbiome development and stability as well as their interactions with their human host. Generally, microbial and human proteins can be extracted and then measured by high performance MS-based proteomics technology. Here, we review the field of human gut microbiome metaproteomics, with a focus on the experimental and informatics considerations involved in characterizing systems ranging from low-complexity model gut microbiota in gnotobiotic mice, to the emerging gut microbiome in the GI tract of newborn human infants, and finally to an established gut microbiota in human adults.

Development of an enhanced metaproteomic approach for deepening the microbiome characterization of the human infant gut.

The establishment of early life microbiota in the human infant gut is highly variable and plays a crucial role in host nutrient availability/uptake and maturation of immunity. Although high-performance mass spectrometry (MS)-based metaproteomics is a powerful method for the functional characterization of complex microbial communities, the acquisition of comprehensive metaproteomic information in human fecal samples is inhibited by the presence of abundant human proteins. To alleviate this restriction, we have designed a novel metaproteomic strategy based on double filtering (DF) the raw samples, a method that fractionates microbial from human cells to enhance microbial protein identification and characterization in complex fecal samples from healthy premature infants. This method dramatically improved the overall depth of infant gut proteome measurement, with an increase in the number of identified low-abundance proteins and a greater than 2-fold improvement in microbial protein identification and quantification. This enhancement of proteome measurement depth enabled a more extensive microbiome comparison between infants by not only increasing the confidence of identified microbial functional categories but also revealing previously undetected categories.

Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities.

Contemporary microbial ecology studies usually employ one or more "omics" approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high-quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other "meta-omic" approaches. The essential, quality-defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein-coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community-biology tool.

Effect of temperature on Chinese rice wine brewing with high concentration presteamed whole sticky rice.

Production of high quality Chinese rice wine largely depends on fermentation temperature. However, there is no report on the ethanol, sugars, and acids kinetics in the fermentation mash of Chinese rice wine treated at various temperatures. The effects of fermentation temperatures on Chinese rice wine quality were investigated. The compositions and concentrations of ethanol, sugars, glycerol, and organic acids in the mash of Chinese rice wine samples were determined by HPLC method. The highest ethanol concentration and the highest glycerol concentration both were attained at the fermentation mash treated at 23 °C. The highest peak value of maltose (90 g/L) was obtained at 18 °C. Lactic acid and acetic acid both achieved maximum values at 33 °C. The experimental results indicated that temperature contributed significantly to the ethanol production, acid flavor contents, and sugar contents in the fermentation broth of the Chinese rice wines.

Cloning and identification of a novel thyroid hormone receptor ß isoform expressed in the pituitary gland.

We have previously identified a novel Trß isoform (TrßΔ) in the rat, in which a novel exon N (108 bps) was found between exon 3 and exon 4 of TrßΔ, which represents the only difference between TrßΔ and Trß1. In this study, we searched for an elongated Trß2-like subtype with one additional exon N. We successfully isolated the entire mRNA/cDNA of a novel elongated Trß2 isoform via PCR in the rat pituitary gland. The mRNA/cDNA was only 108 bps (exon N) longer than that Trß2, and the extension of the sequence was between exon 3 and 4 of Trß. The whole sequence of this novel Trß isoform has been published in NCBI GenBank (HM043807.1); it is named TRbeta2Delta (Trß2Δ). In adult rat pituitary tissue, quantitative real-time RT-PCR analysis showed that the mRNA levels of Trß2Δ and Trß2 were roughly equal (P > 0.05). We cloned, expressed, and purified the His-Trß2Δ protein [recombinant TRß2Δ (rTRß2Δ)]. SDS-PAGE and western blotting revealed that the molecular weight of rTRß2Δ was 58.2 kDa. Using a radioligand binding assay and an electrophoretic mobility shift assay, rTRß2Δ-bound T3 with high affinity and recognized thyroid hormone response element (TRE) binding sites. Finally, in vitro transfection experiments further confirmed that rTRß2Δ binding T3 significantly promotes the transcription of target genes via the TRE. Here, we have provided evidence suggesting that rTRß2Δ is a novel functional TR isoform.