Characterization of extracellular lignocellulolytic enzymes of Coniochaeta sp. during corn stover bioconversion

Biorefinery of renewable lignocellulosic biomass to biochemical and biofuel is a promising technology to mitigate global warming and fuel shortage but hydrolysis of recalcitrant lignocellulose to its constitutive components is the bottleneck of the process. This work isolated and characterized a new lignocellulose degrading filamentous fungus from decomposing wood in mangrove area. The strain was identified as Coniochaeta sp. according to ITS rRNA sequences and its phylogenic analysis. The extracellular lignocellulolytic enzymes of this fungal strain, when grown on corn stover, were profiled by LC–MS/MS and exponentially modified protein abundance index (emPAI) based label-free quantitative proteomics approach. We identified 107 potential lignocellulolytic enzymes and their functional classification revealed unique extracellular enzyme system constituting multienzyme complexes of cellulases (29%), hemicellulases (17%), glycoside hydrolases (10%), proteases and peptidases (24%), lignin degrading enzymes (7%) and hypothetical proteins (13%). The growth behavior, biochemical assay and LC–MS/MS analysis of secretome by isolated fungal strain revealed its lignocellulose degradation potential when cultivated with corn stover as a major carbon source.     

Seasonal changes in nitrogen-cycle gene abundances and in bacterial communities in acidic forest soils

The abundance of genes related to the nitrogen biogeochemical cycle and the microbial community in forest soils (bacteria, archaea, fungi) were quantitatively analyzed via real-time PCR using 11 sets of specific primers amplifying nifH, bacterial amoA, archaeal amoA, narG, nirS, nirK, norB, nosZ, bacterial 16S rRNA gene, archaeal 16S rRNA gene, and the ITS sequence of fungi. Soils were sampled from Bukhan Mountain from September of 2010 to July of 2011 (7 times). Bacteria were the predominant microbial community in all samples. However, the abundance of archaeal amoA was greater than bacterial amoA throughout the year. The abundances of nifH, nirS, nirK, and norB genes changed in a similar pattern, while narG and nosZ appeared in sensitive to the environmental changes. Clone libraries of bacterial 16S rRNA genes were constructed from summer and winter soil samples and these revealed that Acidobacteria was the most predominant phylum in acidic forest soil environments in both samples. Although a specific correlation of environmental factor and gene abundance was not verified by principle component analysis, our data suggested that the combination of biological, physical, and chemical characteristics of forest soils created distinct conditions favoring the nitrogen biogeochemical cycle and that bacterial communities in undisturbed acidic forest soils were quite stable during seasonal change.     

Proteomic analysis of egg white proteins during the early phase of embryonic development

Avian egg albumen participates in embryonic development by providing essential nutrients as well as antimicrobial protection. Although various biological functions of egg white proteins were suggested during embryogenesis, global changes of these proteins under incubation conditions remained uninvestigated. This study presents a proteomic analysis on the change of egg white proteins during the first week of embryonic development. By using 2-DE, together with MALDI-TOF MS/MS, thirty protein spots representing eight proteins were identified showing significant changes in abundance during incubation. An accelerating degradation of ovalbumin was observed in a wide range of molecular weight. In addition, four protein complexes were predicted according to the detected molecular weight increase. Among these speculated protein complexes, an ovalbumin spot coupled with RNA-binding protein was detected. The absence of these protein complexes before incubation, followed by the constant increase in abundance during incubation indicates conceivable pivotal roles in embryonic development. To better understand the function of the proteins identified in this study, discrepancies of egg white protein changes between fertilized and unfertilized chicken eggs were additionally demonstrated. These findings will provide insight into the embryogenesis process to improve our knowledge of egg white proteins in regulating and supporting early embryonic development.     

Distribution of High Bacterial Taxa Across the Chronosequence of Two Alpine Glacier Forelands

Little is known about the changes in abundance of microbial taxa in relation to the chronosequence of receding glaciers. This study investigated how the abundances of ten bacterial phyla or classes varied along successional gradients in two glaciers, Ödenwinkelkees and Rotmoosferner, in the central Alps. Quantitative PCR was used to estimate the abundance of the different bacterial taxa in extended glacier chronosequences, including 10- to 160-year-old successional stages, the surface of the glacier, and a fully established soil. Actinobacteria (15–30%) was the dominant group within the chronosequences. Several taxa showed significant differences in the number of taxa-specific 16S rRNA gene copies per nanogram of DNA and/or in the ratio of taxa-specific to the total bacterial 16S rRNA gene copies (i.e., the relative abundance of the different taxa within the bacterial community) between the established soils or the glacier surface and the 10- to 160-year-old successional stages. A significantly higher proportion of Βetaproteobacteria (20%) was observed on the surface of both glaciers. However, no differences were observed between the 10- to 160-year-old successional stages in the number of taxa-specific 16S rRNA gene copies per nanogram of DNA or in the ratio of taxa-specific to the total bacterial 16S rRNA gene copies for the different taxa. Nevertheless, when the relative abundance data from all the studied taxa were combined and analyzed altogether, most of the sites could be distinguished from one other. This indicates that the overall composition of the bacterial community was more affected than the abundance of the targeted taxa by changes in environmental conditions along the chronosequences.     

Metagenomic analysis of microbial communities across a transect from low to highly hydrocarbon-contaminated soils in King George Island,Maritime Antarctica

Soil samples from a transect from low to highly hydrocarbon-contaminated soils were collected around the Brazilian Antarctic Station Comandante Ferraz (EACF), located at King George Island, Antarctica. Quantitative PCR (qPCR) analysis of bacterial 16S rRNA genes, 16S rRNA gene (iTag), and shotgun metagenomic sequencing were used to characterize microbial community structure and the potential for petroleum degradation by indigenous microbes. Hydrocarbon contamination did not affect bacterial abundance in EACF soils (bacterial 16S rRNA gene qPCR). However, analysis of 16S rRNA gene sequences revealed a successive change in the microbial community along the pollution gradient. Microbial richness and diversity decreased with the increase of hydrocarbon concentration in EACF soils. The abundance of Cytophaga, Methyloversatilis, Polaromonas, and Williamsia was positively correlated (p-value = <.05) with the concentration of total petroleum hydrocarbons (TPH) and/or polycyclic aromatic hydrocarbons (PAH). Annotation of metagenomic data revealed that the most abundant hydrocarbon degradation pathway in EACF soils was related to alkyl derivative-PAH degradation (mainly methylnaphthalenes) via the CYP450 enzyme family. The abundance of genes related to nitrogen fixation increased in EACF soils as the concentration of hydrocarbons increased. The results obtained here are valuable for the future of bioremediation of petroleum hydrocarbon-contaminated soils in polar environments.     

Changes in soil Acidobacteria communities after 2,4,6-trinitrotoluene contamination

Despite their widespread occurrence in soils, the ecology of Acidobacteria and their response to environmental perturbations due to human activities remain very poorly documented. This study was aimed at assessing changes in the diversity and abundance of Acidobacteria in soils contaminated with 2,4,6-trinitrotoluene (TNT) compared with nonpolluted soils. The analysis of Acidobacteria communities at two sites with long-term and short-term contamination revealed that TNT has a drastic impact on the relative abundance of Acidobacteria in soil bacterial 16S rRNA gene libraries. The disappearance of most Acidobacteria from these soils was concomitant with a shift in Acidobacteria community composition and a loss of diversity, although the extent of diversity erosion depended on the sampling site.     

Microbial and Geochemical Assessment of Bauxitic Un-mined and Post-mined Chronosequence Soils from Mocho Mountains, Jamaica

Microorganisms are very sensitive to environmental change and can be used to gauge anthropogenic impacts and even predict restoration success of degraded environments. Here, we report assessment of bauxite mining activities on soil biogeochemistry and microbial community structure using un-mined and three post-mined sites in Jamaica. The post-mined soils represent a chronosequence, undergoing restoration since 1987, 1997, and 2007. Soils were collected during dry and wet seasons and analyzed for pH, organic matter (OM), total carbon (TC), nitrogen (TN), and phosphorus. The microbial community structure was assessed through quantitative PCR and massively parallel bacterial ribosomal RNA (rRNA) gene sequencing. Edaphic factors and microbial community composition were analyzed using multivariate statistical approaches and revealed a significant, negative impact of mining on soil that persisted even after greater than 20?years of restoration. Seasonal fluctuations contributed to variation in measured soil properties and community composition, but they were minor in comparison to long-term effects of mining. In both seasons, post-mined soils were higher in pH but OM, TC, and TN decreased. Bacterial rRNA gene analyses demonstrated a general decrease in diversity in post-mined soils and up to a 3-log decrease in rRNA gene abundance. Community composition analyses demonstrated that bacteria from the Proteobacteria (α, β, γ, δ), Acidobacteria, and Firmicutes were abundant in all soils. The abundance of Firmicutes was elevated in newer post-mined soils relative to the un-mined soil, and this contrasted a decrease, relative to un-mined soils, in proteobacterial and acidobacterial rRNA gene abundances. Our study indicates long-lasting impacts of mining activities to soil biogeochemical and microbial properties with impending loss in soil productivity.     

Initial Copper Stress Strengthens the Resistance of Soil Microorganisms to a Subsequent Copper Stress

To improve the prediction of essential ecosystem functioning under future environmental disturbances, it is of significance to identify responses of soil microorganisms to environmental stresses. In this study, we collected polluted soil samples from field plots with eight copper levels ranging from 0 to 3,200 mg Cu kg^?1 soil. Then, the soils with 0 and 3,200 mg Cu kg^?1 were selected to construct a microcosm experiment. Four treatments were set up including Cu0-C and Cu3200-C without further Cu addition, and Cu0-A and Cu3200-A with addition of 57.5 mg Cu kg^?1 soil. We measured substrate-induced respiration (SIR) and potential nitrification rate (PNR). Furthermore, the abundance of bacterial, archaeal 16S rRNA genes, ammonia-oxidizing bacteria and archaea amoA genes were determined through quantitative PCR. The soil microbial communities were investigated by terminal restriction fragment length polymorphism (T-RFLP). For the field samples, the SIR and PNR as well as the abundance of soil microorganisms varied significantly between eight copper levels. Soil microbial communities highly differed between the low and high copper stress. In the microcosm experiment, the PNR and SIR both recovered while the abundance of soil microorganisms varied irregularly during the 90-day incubation. The differences of microbial communities measured by pairwise Bray–Curtis dissimilarities between Cu0-A and Cu0-C on day 0 were significantly higher after subsequent stress than before. However, the differences of microbial communities between Cu3200-A and Cu3200-C on day 0 changed little between after subsequent stress and before. Therefore, initial copper stress could increase the resistance of soil microorganisms to subsequent copper stress.     

Dissimilar responses of fungal and bacterial communities to soil transplantation simulating abrupt climate changes

Both fungi and bacteria play essential roles in regulating soil carbon cycling. To predict future carbon stability, it is imperative to understand their responses to environmental changes, which is subject to large uncertainty. As current global warming is causing range shifts toward higher latitudes, we conducted three reciprocal soil transplantation experiments over large transects in 2005 to simulate abrupt climate changes. Six years after soil transplantation, fungal biomass of transplanted soils showed a general pattern of changes from donor sites to destination, which were more obvious in bare fallow soils than in maize cropped soils. Strikingly, fungal community compositions were clustered by sites, demonstrating that fungi of transplanted soils acclimatized to the destination environment. Several fungal taxa displayed sharp changes in relative abundance, including Podospora, Chaetomium, Mortierella and Phialemonium. In contrast, bacterial communities remained largely unchanged. Consistent with the important role of fungi in affecting soil carbon cycling, 8.1%–10.0% of fungal genes encoding carbon‐decomposing enzymes were significantly (p < 0.01) increased as compared with those from bacteria (5.7%–8.4%). To explain these observations, we found that fungal occupancy across samples was mainly determined by annual average air temperature and rainfall, whereas bacterial occupancy was more closely related to soil conditions, which remained stable 6 years after soil transplantation. Together, these results demonstrate dissimilar response patterns and resource partitioning between fungi and bacteria, which may have considerable consequences for ecosystem‐scale carbon cycling.     

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.     

A proteomics approach to investigate the process of Zn hyperaccumulation in Noccaea caerulescens (J & C. Presl) F.K. Meyer

Zinc (Zn) is an essential trace element in all living organisms, but is toxic in excess. Several plant species are able to accumulate Zn at extraordinarily high concentrations in the leaf epidermis without showing any toxicity symptoms. However, the molecular mechanisms of this phenomenon are still poorly understood. A state‐of‐the‐art quantitative 2D liquid chromatography/tandem mass spectrometry (2D‐LC‐MS/MS) proteomics approach was used to investigate the abundance of proteins involved in Zn hyperaccumulation in leaf epidermal and mesophyll tissues of Noccaea caerulescens. Furthermore, the Zn speciation in planta was analyzed by a size‐exclusion chromatography/inductively coupled plasma mass spectrometer (SEC‐ICP‐MS) method, in order to identify the Zn‐binding ligands and mechanisms responsible for Zn hyperaccumulation. Epidermal cells have an increased capability to cope with the oxidative stress that results from excess Zn, as indicated by a higher abundance of glutathione S‐transferase proteins. A Zn importer of the ZIP family was more abundant in the epidermal tissue than in the mesophyll tissue, but the vacuolar Zn transporter MTP1 was equally distributed. Almost all of the Zn located in the mesophyll was stored as Zn–nicotianamine complexes. In contrast, a much lower proportion of the Zn was found as Zn–nicotianamine complexes in the epidermis. However, these cells have higher concentrations of malate and citrate, and these organic acids are probably responsible for complexation of most epidermal Zn. Here we provide evidence for a cell type‐specific adaptation to excess Zn conditions and an increased ability to transport Zn into the epidermal vacuoles.     

Predictable bacterial composition and hydrocarbon degradation in Arctic soils following diesel and nutrient disturbance

Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with <10% organic matter, while Proteobacteria dominated higher-organic matter soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future.     

Sorting signals, N-terminal modifications and abundance of the chloroplast proteome

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that 'spectral counting' can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models.     

Intra-Genomic Variation in the Ribosomal Repeats of Nematodes

Ribosomal loci represent a major tool for investigating environmental diversity and community structure via high-throughput marker gene studies of eukaryotes (e.g. 18S rRNA). Since the estimation of species’ abundance is a major goal of environmental studies (by counting numbers of sequences), understanding the patterns of rRNA copy number across species will be critical for informing such high-throughput approaches. Such knowledge is critical, given that ribosomal RNA genes exist within multi-copy repeated arrays in a genome. Here we measured the repeat copy number for six nematode species by mapping the sequences from whole genome shotgun libraries against reference sequences for their rRNA repeat. This revealed a 6-fold variation in repeat copy number amongst taxa investigated, with levels of intragenomic variation ranging from 56 to 323 copies of the rRNA array. By applying the same approach to four C. elegans mutation accumulation lines propagated by repeated bottlenecking for an average of ~400 generations, we find on average a 2-fold increase in repeat copy number (rate of increase in rRNA estimated at 0.0285-0.3414 copies per generation), suggesting that rRNA repeat copy number is subject to selection. Within each Caenorhabditis species, the majority of intragenomic variation found across the rRNA repeat was observed within gene regions (18S, 28S, 5.8S), suggesting that such intragenomic variation is not a product of selection for rRNA coding function. We find that the dramatic variation in repeat copy number among these six nematode genomes would limit the use of rRNA in estimates of organismal abundance. In addition, the unique pattern of variation within a single genome was uncorrelated with patterns of divergence between species, reflecting a strong signature of natural selection for rRNA function. A better understanding of the factors that control or affect copy number in these arrays, as well as their rates and patterns of evolution, will be critical for informing estimates of global biodiversity.     

Proteomics of Arabidopsis redox proteins in response to methyl jasmonate

Protein redox regulation is increasingly recognized as an important switch of protein activity in yeast, bacteria, mammals and plants. In this study, we identified proteins with potential thiol switches involved in jasmonate signaling, which is essential for plant defense. Methyl jasmonate (MeJA) treatment led to enhanced production of hydrogen peroxide in Arabidopsis leaves and roots, indicating in vivo oxidative stress. With monobromobimane (mBBr) labeling to capture oxidized sulfhydryl groups and 2D gel separation, a total of 35 protein spots that displayed significant redox and/or total protein expression changes were isolated. Using LC–MS/MS, the proteins in 33 spots were identified in both control and MeJA-treated samples. By comparative analysis of mBBr and SyproRuby gel images, we were able to determine many proteins that were redox responsive and proteins that displayed abundance changes in response to MeJA. Interestingly, stress and defense proteins constitute a large group that responded to MeJA. In addition, many cysteine residues involved in the disulfide dynamics were mapped based on tandem MS data. Identification of redox proteins and their cysteine residues involved in the redox regulation allows for a deeper understanding of the jasmonate signaling networks.     

Quantitative proteomic profiling of pancreatic cancer juice

Pancreatic juice is an exceptionally rich source of cancer-specific proteins shed from cancerous ductal cells into the pancreatic juice. Quantitative proteomic analysis of the proteins specific to pancreatic cancer juice has not previously been reported. We used isotope-code affinity tag (ICAT) technology and MS/MS to perform quantitative protein profiling of pancreatic juice from pancreatic cancer patients and normal controls. ICAT technology coupled with MS/MS allows the systematic study of the proteome and measures the protein abundance in pancreatic juice with the potential for development of biomarkers. A total of 105 proteins were identified and quantified in the pancreatic juice from a pancreatic cancer patient, of which 30 proteins showed abundance changes of at least twofold in pancreatic cancer juice compared to normal controls. Many of these proteins have been externally validated. This is the first comprehensive study of the pancreatic juice proteome by quantitative global protein profiling, and the study reveals numerous proteins that are shown for the first time to be associated with pancreatic cancer, providing candidates for diagnostic biomarkers. One of the identified proteins, insulin-like growth factor binding protein-2 was further validated by Western blotting to be elevated in pancreatic cancer juice and overexpressed in pancreatic cancer tissue.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

Affinity enrichment for mass spectrometry: improving the yield of low abundance biomarkers

Introduction: Mass spectrometry (MS) is the premier tool for discovering novel disease-associated protein biomarkers. Unfortunately, when applied to complex body fluid samples, MS has poor sensitivity for the detection of low abundance biomarkers (?10 ng/mL), derived directly from the diseased tissue cells or pathogens.

Areas covered: Herein we discuss the strengths and drawbacks of technologies used to concentrate low abundance analytes in body fluids, with the aim to improve the effective sensitivity for MS discovery. Solvent removal by dry-down or dialysis, and immune-depletion of high abundance serum or plasma proteins, is shown to have disadvantages compared to positive selection of the candidate biomarkers by affinity enrichment. A theoretical analysis of affinity enrichment reveals that the yield for low abundance biomarkers is a direct function of the binding affinity (Association/Dissociation rates) used for biomarker capture. In addition, a high affinity capture pre processing step can effectively dissociate the candidate biomarker from partitioning with high abundance proteins such as albumin.

Expert commentary: Properly designed high affinity capture materials can enrich the yield of low abundance (0.1–10 picograms/mL) candidate biomarkers for MS detection. Affinity capture and concentration, as an upfront step in sample preparation for MS, combined with MS advances in software and hardware that improve the resolution of the chromatographic separation can yield a transformative new class of low abundance biomarkers predicting disease risk or disease latency.