Comparison of long- and short-read metagenomic assembly for low-abundance species and resistance genes.

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

Application of next-generation sequencing in the detection of low-abundance mutations.

Mutation accumulation in somatic cells contributes to cancer development, aging and many non-malignant diseases. The true mutation frequency in normal cells is extremely low, which presents a challenge in detecting these mutations at such low frequencies. The emergence of next-generation sequencing (NGS) technology enables direct detection of rare mutations across the entire genome of any species. This breakthrough overcomes numerous limitations of traditional mutation detection techniques that rely on specific detection models and sites. However, conventional NGS is limited in its application for detecting low-frequency mutations due to its high sequencing error rate. To address this challenge, high-accuracy NGS sequencing techniques based on molecular consensus sequencing strategies have been developed. These techniques have the ability to correct sequencing errors, resulting in error rates lower than 10-7, are expected to serve as effective tools for low-frequency mutation detection. Error-corrected NGS (ecNGS) techniques hold great potential in various areas, including safety evaluation and research on environmental mutagens, risk assessment of cell and gene therapy drugs, population health risk monitoring, and fundamental research in life sciences. This review highlights a comprehensive review of the research progress in low-frequency mutation detection techniques based on NGS, and provides a glimpse into their potential applications. It also offers an outlook on the potential applications of these techniques, thereby providing valuable insights for further development, research, and application of this technology in relevant fields.

Translocation of vaginal and cervical low-abundance non-Lactobacillus bacteria notably associate with endometriosis: A pilot study.

The etiology remains to be understood for endometriosis (EMS) which affected health negatively for 10% of reproductive-age women globally. Emerging studies found the associations of EMS with genital microbiota dysbiosis. However, the role of vaginal and cervical microbiota is not fully understood for Chinese women. This study recruited forty Chinese women (21 healthy women and 19 EMS patients) to analyze vaginal and cervical microbiota using 16S rRNA amplicon sequencing method. For both sites, there were no significant differences for distribution of microbial samples between control and EMS group, which was concordant with dominated Lactobacillus in both groups. In contrast, we observed accumulation of several low-abundance genera in vaginal and cervical microbiota of EMS patients, such as Fannyhessea, Prevotella, Streptococcus, Bifidobacterium, Veillonella, Megasphaera and Sneathia. Random forest analysis found that translocation of these genera had the significant importance in differentiating EMS patients from controls. In addition, cervix/vagina ratio of these genera also associated with EMS severity. And these genera had notable associations with ascending infection-related functional pathways, including flagellar assembly, bacterial motility proteins, bacterial toxins and epithelial cell signaling in Helicobacter pylori infection. These findings suggest that translocation of specific genera between vaginal and cervical sites play a role in EMS.

Low-Abundance Protein Enrichment for Medical Applications: The Involvement of Combinatorial Peptide Library Technique.

The discovery of low- and very low-abundance proteins in medical applications is considered a key success factor in various important domains. To reach this category of proteins, it is essential to adopt procedures consisting of the selective enrichment of species that are present at extremely low concentrations. In the past few years pathways towards this objective have been proposed. In this review, a general landscape of the enrichment technology situation is made first with the presentation and the use of combinatorial peptide libraries. Then, a description of this peculiar technology for the identification of early-stage biomarkers for well-known pathologies with concrete examples is given. In another field of medical applications, the determination of host cell protein traces potentially present in recombinant therapeutic proteins, such as antibodies, is discussed along with their potentially deleterious effects on the health of patients on the one hand, and on the stability of these biodrugs on the other hand. Various additional applications of medical interest are disclosed for biological fluids investigations where the target proteins are present at very low concentrations (e.g., protein allergens).

On possible trypsin-induced biases in peptides analysis with aerolysin nanopore.

Nanopore-based single-molecule analysis technique is a promising approach in the field of proteomics. In this Technical Brief, the interaction between the biological nanopore of Aerolysin (AeL) and peptides is investigated, focusing on potential biases depending on the AeL activation protocol. Our results reveal that residual trypsin, which may be unintentionally introduced in analyte solution when using a classical AeL activation protocol, can induce a significant formation of shorter peptides by enzymatic degradation of longer ones, which may lead to unwanted effects and/or misinterpretations. AeL free-trypsin activation protocol eliminates this bias and appears more appropriate for peptide/proteins analysis, specifically in the perspective of nanopore-based molecular fingerprinting or of low-abundance species characterization.

Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi.

An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed "1DE-gel concentration" method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC-MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

Combinatorial peptides: A library that continuously probes low-abundance proteins.

After a decade of experimental applications, it is the objective of this review to make a point on combinatorial peptide ligand libraries dedicated to low-abundance proteins from animals to plants and to microorganism proteomics. It is, thus, at the light of the recent technical developments and applications that we will examine the state of the art, its usage within the scientific community, and its openness to unexplored fields. The improvements of the methodology and its implementation in connection with analytical determinations of combinatorial peptide ligand library (CPLL)-treated samples are extensively reviewed and commented upon. Relevant examples covering few critical aspects describe the performance of the technology. Finally, a reflection on the technological future is attempted in particular by involving new concepts adapted to the limited availability of certain biological samples.

Allee effects and the Allee-effect zone in northwest Atlantic cod.

According to the theory of compensatory dynamics, depleted populations should recover when the threat responsible for their decline is removed because per capita population growth is assumed to be highest when populations are at their smallest viable sizes. Yet, many seriously depleted fish populations have failed to recover despite threat mitigation. Atlantic cod (Gadus morhua) stocks off Newfoundland, despite 30 years of dramatically reduced fishing mortality and numerous fishery closures, have not recovered, suggesting that drivers other than fishing can regulate the growth of collapsed fish populations, inhibiting or preventing their recovery. Here, using Bayesian inference, we show strong evidence of Allee effects in a south Newfoundland cod population, based on data on recruitment and spawning stock biomass. We infer the Allee-effect threshold, below which recovery is impaired. We demonstrate the necessity of data at low population sizes to make inferences about the nature of low-abundance dynamics. Our work indicates that Allee effects are not negligible in commercially exploited fish populations, as commonly projected, and that they represent an inhibitory force that can effectively prevent recovery from overfishing. Our findings contrast with prevailing fisheries management practices that assume compensatory dynamics at low abundances with potential to seriously overestimate the recovery potential of collapsed populations.

The associations between intestinal bacteria of Eospalax cansus and soil bacteria of its habitat.

BACKGROUND: Intestinal bacteria of mammal can be influenced by many factors, environmental bacteria is an important factor. However, there are few studies on the interactions between environmental bacteria and intestinal bacteria in wild mammals. To explore the associations between the intestinal bacteriome and the related environmental bacteriome, the intestinal bacterial communities of Eospalax cansus at three different sites and the bacterial communities of the surrounding soil (outside and inside the cave) at each site were investigated by 16S rRNA sequencing. RESULTS: The composition and structure between zokor intestinal bacteria and related soil bacteria were distinct, and the soil of zokor habitat harbored significantly higher diversity than that of zokor intestinal bacteria. We have found that host factors may be more important than environmental factors in shaping intestinal bacteriome. In addition, it was found that the relative abundances of shared OTUs between zokors and related soil were significantly negatively related. These shared OTUs were present in the soil at relatively low abundance. However, these shared OTUs between zokors and soil were affiliated with diverse bacterial taxa, and they were related to the degradation of complex carbohydrates. CONCLUSIONS: These results suggested that the zokor gut may mainly select for low-abundance but diverse soil bacteria, which may be a host- specific choice for zokor to meet the needs of its phytophagous dietary.

Development and Provisional Validation of a Multiplex LC-MRM-MS Test for Timely Kidney Injury Detection in Urine.

Kidney injury is a complication frequently encountered in hospitalized patients. Early detection of kidney injury prior to loss of renal function is an unmet clinical need that should be targeted by a protein-based biomarker panel. In this study, we aim to quantitate urinary kidney injury biomarkers at the picomolar to nanomolar level by liquid chromatography coupled to tandem mass spectrometry in multiple reaction monitoring mode (LC-MRM-MS). Proteins were immunocaptured from urinary samples, denatured, reduced, alkylated, and digested into peptides before LC-MRM-MS analysis. Stable-isotope-labeled peptides functioned as internal standards, and biomarker concentrations were attained by an external calibration strategy. The method was evaluated for selectivity, carryover, matrix effects, linearity, and imprecision. The LC-MRM-MS method enabled the quantitation of KIM-1, NGAL, TIMP2, IGFBP7, CXCL9, nephrin, and SLC22A2 and the detection of TGF-ß1, cubilin, and uromodulin. Two to three peptides were included per protein, and three transitions were monitored per peptide for analytical selectivity. The analytical carryover was <1%, and minimal urine matrix effects were observed by combining immunocapture and targeted LC-MRM-MS analysis. The average total CV of all quantifier peptides was 26%. The linear measurement range was determined per measurand and found to be 0.05-30 nmol/L. The targeted MS-based method enables the multiplex quantitation of low-abundance urinary kidney injury biomarkers for future clinical evaluation.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Optimization of library preparation based on SMART for ultralow RNA-seq in mice brain tissues.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides new insights to address biological and medical questions, and it will benefit more from the ultralow input RNA or subcellular sequencing. RESULTS: Here, we present a highly sensitive library construction protocol for ultralow input RNA sequencing (ulRNA-seq). We systematically evaluate experimental conditions of this protocol, such as reverse transcriptase, template-switching oligos (TSO), and template RNA structure. It was found that Maxima H Minus reverse transcriptase and rN modified TSO, as well as all RNA templates capped with m7G improved the sequencing sensitivity and low abundance gene detection ability. RNA-seq libraries were successfully prepared from total RNA samples as low as 0.5 pg, and more than 2000 genes have been identified. CONCLUSIONS: The ability of low abundance gene detection and sensitivity were largely enhanced with this optimized protocol. It was also confirmed in single-cell sequencing, that more genes and cell markers were identified compared to conventional sequencing method. We expect that ulRNA-seq will sequence and transcriptome characterization for the subcellular of disease tissue, to find the corresponding treatment plan.

Low-Abundance Drug-Resistant HIV-1 Variants in Antiretroviral Drug-Naive Individuals: A Systematic Review of Detection Methods, Prevalence, and Clinical Impact.

BACKGROUND: The presence of high-abundance drug-resistant HIV-1 jeopardizes success of antiretroviral therapy (ART). Despite numerous investigations, the clinical impact of low-abundance drug-resistant HIV-1 variants (LA-DRVs) at levels <15%-25% of the virus population in antiretroviral (ARV) drug-naive individuals remains controversial. METHODS: We systematically reviewed 103 studies assessing prevalence, detection methods, technical and clinical detection cutoffs, and clinical significance of LA-DRVs in antiretroviral drug-naive adults. RESULTS: In total, 14 919 ARV drug-naive individuals were included. Prevalence of LA-DRVs (ie, proportion of individuals harboring LA-DRVs) was 0%-100%. Technical detection cutoffs showed a 4 log range (0.001%-10%); 42/103 (40.8%) studies investigating the impact of LA-DRVs on ART; 25 studies included only individuals on first-line nonnucleoside reverse transcriptase inhibitor-based ART regimens. Eleven of those 25 studies (44.0%) reported a significantly association between preexisting LA-DRVs and risk of virological failure whereas 14/25 (56.0%) did not. CONCLUSIONS: Comparability of the 103 studies is hampered by high heterogeneity of the studies' designs and use of different methods to detect LA-DRVs. Thus, evaluating clinical impact of LA-DRVs on first-line ART remains challenging. We, the WHO HIVResNet working group, defined central areas of future investigations to guide further efforts to implement ultrasensitive resistance testing in routine settings.

FRACPRED-2D-PRM: A Fraction Prediction Algorithm-Assisted 2D Liquid Chromatography-Based Parallel Reaction Monitoring-Mass Spectrometry Approach for Measuring Low-Abundance Proteins in Human Plasma.

Multidimensional fractionation-based enrichment methods improve the sensitivity of proteomic analysis for low-abundance proteins. However, a major limitation of conventional multidimensional proteomics is the extensive labor and instrument time required for analyzing many fractions obtained from the first dimension separation. Here, a fraction prediction algorithm-assisted 2D LC-based parallel reaction monitoring-mass spectrometry (FRACPRED-2D-PRM) approach for measuring low-abundance proteins in human plasma is presented. Plasma digests are separated by the first dimension high-pH RP-LC with data-dependent acquisition (DDA). The FRACPRED algorithm is then usedto predict the retention times of undetectable target peptides according to those of other abundant plasma peptides during the first dimension separation. Fractions predicted to contain target peptides are analyzed by the second dimension low-pH nano RP-LC PRM. The accuracy and robustness of fraction prediction with the FRACPRED algorithm are demonstrated by measuring two low-abundance proteins, aldolase B and carboxylesterase 1, in human plasma. The FRACPRED-2D-PRM proteomics approach demonstrates markedly improved efficiency and sensitivity over conventional 2D-LC proteomics assays. It is expected that this approach will be widely used in the study of low-abundance proteins in plasma and other complex biological samples.

Purification of low-abundance lysozyme in egg white via free-flow electrophoresis with gel-filtration chromatography.

As an effective separation tool, free-flow electrophoresis has not been used for purification of low-abundance protein in complex sample matrix. Herein, lysozyme in complex egg white matrix was chosen as the model protein for demonstrating the purification of low-content peptide via an FFE coupled with gel fitration chromatography (GFC). The crude lysozyme in egg while was first separated via free-flow zone electrophoresis (FFZE). After that, the fractions with lysozyme activity were condensed via lyophilization. Thereafter, the condensed fractions were further purified via a GFC of Sephadex G50. In all of the experiments, a special poly(acrylamide- co-acrylic acid) (P(AM-co-AA)) gel electrophoresis and a mass spectrometry were used for identification of lysozyme. The conditions of FFZE were optimized as follows: 130 µL/min sample flow rate, 4.9 mL/min background buffer of 20 mM pH 5.5 Tris-Acetic acid, 350 V, and 14 °C as well as 2 mg/mL protein content of crude sample. It was found that the purified lysozyme had the purity of 80% and high activity as compared with its crude sample with only 1.4% content and undetectable activity. The recoveries in the first and second separative steps were 65% and 82%, respectively, and the total recovery was about 53.3%. The reasons of low recovery might be induced by diffusion of lysozyme out off P(AM-co-AA) gel and co-removing of high-abundance egg ovalbumin. All these results indicated FFE could be used as alternative tool for purification of target solute with low abundance.

Insight of low-abundance proteins in rice leaves under Cd stress using combinatorial peptide ligand library technology.

Low-abundance proteins (LAPs) play a very important role in interaction, regulation, and metabolism of plant biological processes. A combinatorial peptide ligand library (CPLL) can solve the problem of high-abundance proteins (HAPs) masking LAPs and enlarging the dynamic range of protein concentrations perfectly and be considered as one of the most advanced approaches for plant proteomics research. In this paper, a proper CPLL method to rice leaf proteins was established for the first time and 1056 proteins were identified in rice leaf extracts, and 624 (59.1%) LAPs were newly detected after CPLL. Based on this technology, we detected the response of rice to Cd stress and analyzed the differential LAPs and the biological significance of misexpressed proteins before and after Cd stress by bioinformatics analysis. An important contribution has also been made to a better understanding of the complex mechanisms by which rice adapts to Cd stress. Graphical abstract.

Characterization of the colostrum and transition milk proteomes from primiparous and multiparous Holstein dairy cows.

Colostrum plays a vital role in the nutrition, development, and immunity of a newborn calf. This study aimed to characterize the protein profile of colostrum and to identify changes in the colostrum proteome across parity during the transition to mature milk. Colostrum and transition milk samples were collected at milkings 1, 2, 4, and 14 after calving from multiparous (n = 10) and primiparous cows (n = 10). Samples were skimmed, fractionated, and enriched before analysis for low-abundance proteins by liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Changes in protein abundances were analyzed using PROC MIXED in SAS (SAS Institute Inc., Cary, NC) with determination of the adaptive false discovery rate adjustment using a MULTTEST procedure to identify effects of parity (P), milking number (MN), and their interaction (MN×P). We identified 86 proteins through LC-MS/MS, including 3 low-abundance proteins that were affected by P, 78 that were affected by MN, and 36 affected by MN×P. Prominent ontological groupings of proteins affected by MN included defense or immunity proteins, such as immunoglobulins. Proteins involved in the plasminogen activating cascade and more broadly, blood coagulation, were affected by MN×P. The results of this study add to increasing knowledge of the colostrum and transition milk proteomes, and this is the first study to find evidence of different abundances of these proteins when examined across P, MN, and MN×P. These findings aid in the identification of potential milk protein biomarkers for mammary health during the early postpartum period.

Coacervation of Lipid Bilayer in Natural Cell Membranes for Extraction, Fractionation, and Enrichment of Proteins in Proteomics Studies.

This is the first report where hexafluoroisopropanol (HFIP) was used to induce the coacervation of lipid components in natural cell membranes that would concomitantly result in solubilization, extraction, and enrichment of hydrophobic proteins (e.g., integral membrane proteins, IMP) into the coacervate phase, and extraction of hydrophilic proteins in a separate aqueous phase. The incorporation of this innovative approach in the proteomics workflow would allow the fractionation of proteins in separate aqueous and coacervate phases and would also eliminate the need for using surfactants. Subsequently, proteins can be identified by the bottom-up proteomics approach where samples were digested in solution after phase separation. Yeast cell wall proteins, anchored membrane proteins, and proteins related to some regulatory activities were mostly found in the aqueous-rich phase. On the other hand, most integral membrane proteins, proteins involved in metabolic processes, and proteins responsible for ions or drug binding were identified in the coacervate phase. The detergent-free, facile, and rapid process of natural lipid coacervation increased the number of identified proteins by 8% (vs no-phase separation experiment). The identification of all IMPs and organelle IMPs was improved by 13% and 29%, respectively. In addition, 25% more low-abundance proteins (less than 20 ppm) were identified.

Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins.

Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.

Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach.

Introduction: The last decade has yielded significant developments in the field of proteomics, especially in mass spectrometry (MS) and data analysis tools. In particular, a shift from gel-based to MS-based proteomics has been observed, thereby providing a platform with which to construct proteome atlases for all life forms. Nevertheless, the analysis of plant proteomes, especially those of samples that contain high-abundance proteins (HAPs), such as soybean seeds, remains challenging. Areas covered: Here, we review recent progress in soybean seed proteomics and highlight advances in HAPs depletion methods and peptide pre-fractionation, identification, and quantification methods. We also suggest a pipeline for future proteomic analysis, in order to increase the dynamic coverage of the soybean seed proteome. Expert opinion: Because HAPs limit the dynamic resolution of the soybean seed proteome, the depletion of HAPs is a prerequisite of high-throughput proteome analysis, and owing to the use of two-dimensional gel electrophoresis-based proteomic approaches, few soybean seed proteins have been identified or characterized. Recent advances in proteomic technologies, which have significantly increased the proteome coverage of other plants, could be used to overcome the current complexity and limitation of soybean seed proteomics.