All datasets generated for this study are included in the manuscript with the exception of the rhesus macaque metabolics data which is included as Table S6. There remains a pressing need for biomarkers that can predict who will progress to active tuberculosis TB after exposure to Mycobacterium tuberculosis MTB bacterium. By analyzing cohorts of household contacts of TB index cases HHCs and a stringent non-human primate NHP challenge model, we evaluated whether integration of blood transcriptional profiling with serum metabolomic profiling can provide new understanding of disease processes and enable improved prediction of TB progression. Compared to either alone, the combined application of pre-existing transcriptome- and metabolome-based signatures more accurately predicted TB progression in the HHC cohorts and more accurately predicted disease severity in the NHPs.
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Metrics details. As a ubiquitous filamentous fungal, Aspergillus spp. Nevertheless, the production of various extracellular enzymes can be influenced by different factors including nitrogen source, carbon source, cultivation temperature, and initial pH value.
Thus, this study aims to reveal how amino acids affect the decomposition of lignocellulose by Aspergillus fumigatus Z5 through transcriptional and proteomics methods. The activities of several lignocellulosic enzymes secreted by A. The peak of endo-glucanase 7. The secretomes of A. Correlation analysis results of transcriptome and proteome data with fermentation profiles showed that most of the cellulose-degrading enzymes including cellulases, hemicellulases and glycoside hydrolases were highly upregulated when cysteine was added to the growth medium.
In particular, the enzymes that convert cellulose into cellobiose appear to be upregulated. This study could increase knowledge of lignocellulose bioconversion pathways and fungal genetics. The possible reason for these results is that Z5 preferred to use amino acids such as cysteine to adapt to the external environment through upregulating carbon-related metabolism pathways.
Various saprotrophic filamentous fungi own a considerable capacity of lignocellulose-degrading efficiency, which is considered as the most abundant natural materials, and it is the most abundant resource present in a variety of plants that humans can easily access and use. The growing focus on depleting fossil fuels requires a shift from nonrenewable carbon sources to renewable biological resources such as lignocellulose.
Regardless of the cause, lignocellulosic materials consist of three main polymers: cellulose a glucose homopolymer , hemicellulose, heteropolymers of pentoses and hexoses , and lignin phenyls, amorphous polymers [ 1 ]. Approximately billion tons of cellulose are produced annually by plants, making this polysaccharide a substantial organic carbon pool on earth [ 2 ]. It is one of the most widely distributed and most abundant substances on earth and one of the cheapest renewable resources.
Plant cellulose is mainly degraded by various microorganisms into organic carbon sources and then transformed into the most substantial material flows in the biosphere. Therefore, the importance of cellulose as a renewable energy source has become the subject of research and commerce.
Nevertheless, the critical step in the use of cellulose is its hydrolysis into monomeric sugars and its eventual conversion to valuable chemicals and energy [ 3 ]. Lignocellulolytic enzymes are a series of enzymes related to lignocellulose degradation, including pectinases, cellulases, hemicellulases, manganese peroxidase MnP , lignin peroxidase LiP , and laccase Lac , [ 4 ].
As the major components of lignocellulolytic enzymes, cellulase consists of at least three types of enzymes: endo-glucanases EC 3.
Enzymes degrading the hemicelluloses called hemicellulases are well characterized, and are classified according to their substrate specificities, such as xylanase, lichenase, and laminarinase. Pectinase is an enzyme that can break down pectin. The degradation of lignocellulose requires the synergistic action of all these enzymes mentioned above, especially cellulases and hemicellulases. Most of the hydrolytic enzymes are secreted by various microbes, including bacteria, actinomycetes, and filamentous fungi, which have been screened from various habitats [ 1 , 6 ].
Among the different methods of utilizing lignocellulose, microbial degradation technology has attracted a large amount of attention worldwide because of its advantages of having low cost, employing mild reaction conditions, and lack of pollution to the environment [ 7 ].
Due to high extracellular enzymatic activity and a relatively large number of enzymatic species, fungi have a considerable capacity to degrade cellulose. Meanwhile, the fungi can contribute significantly to recycling lignocellulosic biomass due to their capacities of secreting a large number of lignocellulolytic enzymes [ 8 ].
Therefore, filamentous fungi, including Trichoderma , Aspergillus , Penicillium , Acremonium , Myrothecium , Neurospora , and Chaetomium , have been extensively applied in the cellulose industry. In addition, A. Many studies on the microbial degradation of lignocellulose have mainly focused on microbial resources, enzyme properties and synthetic regulation, and enzyme genetic engineering [ 11 , 12 ].
However, selection of the specific nutritional factors that influence the biodegradation ability of lignocellulosic fungi and its concrete mechanisms is still rarely reported at present. Nitrogen sources are indispensable during the secretion process of various extracellular enzymes by A. Here, amino acids were added into culture medium containing rice straw powder, and the effect of amino acids on the cellulose production of A. Transcriptomics can help reveal a synergistic response of a fungal strain to the external environment and nutritional changes, and proteomics is a useful tool to discover profile and identify various proteins in response to special environment.
The objective of this study is to reveal how amino acids cysteine and methionine affect lignocellulose biodegradation by the efficient lignocellulose-degrading strain A. Overall findings improve our knowledge of the biodegradation mechanisms of lignocellulosic fungi, and it is anticipated that this knowledge will have benefits for the development of biofuel production. Various pure amino acids as indicated in the experimental procedures were used as specific nutritional factors to evaluate the biodegradation of rice straw by A.
The changes in enzyme activities were mainly consistent among different treatments. On the other hand, different concentrations of cysteine and methionine 0. The results indicated that the optimum concentrations for endo-glucanase and exo-glucanase activities were 1.
Meanwhile, the optimum concentration for a negative effect on all the detected enzyme activities was 2. Therefore, cysteine and methionine were chosen for further investigation for their effects on the biodegradation of lignocellulose by A.
Activities of extracellular hydrolytic enzymes in the secretome of A. Mycelial growth was more extensive in the Cys treatment than in the CK treatment. However, mycelial growth is minimal and almost invisible in the Met treatment Additional file 1 : Figure S1.
The highest biomass was obtained in the Cys treatment Samples from different treatments were taken to compare the change of the surface through scanning electron microscopy SEM. The xylem and cell wall ultrastructure with tracheid-bordered pits could be observed in raw materials data not shown. Samples from different treatments were also observed, and the results are shown in Fig.
Under the influence of cysteine, the decomposition effect of rice straw was better than that of CK, and the internal structure was visible with a large number of holes appearing on the surface. Moreover, fungal hyphae could directly enter the interior of the rice straw, resulting in easier decomposition. In the Met treatment, the surface of the rice straw was substantially unchanged compared to the raw materials, and only small cracks produced by Z5 acting on the straw surface could be observed.
All enzyme activities in Met were significantly lower than those in CK, including endo-glucanase 2. Growth and extracellular hydrolytic enzyme activities of A.
Secretomes from A. The number of specific proteins in different lanes was detected, among which Sect. A total of proteins were detected for CK, proteins were identified for Cys, and proteins were detected for Met. Thirty-six, , and 6 proteins were identified as unique for control treatment, cysteine treatment, and methionine treatment, respectively.
As depicted in Fig. The complete list of proteins secreted by Z5 is presented in Additional file 1 : Table S1. A significant portion of the identified proteins in this study was hypothetical proteins or with an unknown function, which meant that the peptide sequence matched either an ORF that had not previously been shown to be expressed or a protein with unknown function.
Moreover, the remainder of the identified proteins were functionally diverse such as oxidoreductase and transferase. In particular, only Cys contained a significant amount of oxidoreductase compared to the other treatments Fig. The identified secretomes from A. A total of proteins containing signal peptides were identified in the secretomes, and most of the proteins were involved in lignocellulose degradation. All of the proteins identified in the extracellular crude enzymes contained a signal peptide, and the total number of cellulases, hemicellulases, and chitinases was In addition to the several enzymes mentioned above, 11 pectin lyases were identified, and some esterases, catalases, and transferases were also detected.
All of the proteins with signal peptides were separated into five different sections according to molecular size, and most of the lignocellulosic enzymes were distributed in Sect. Afterward, the specific proteins in each treatment were also evaluated to discover critical enzymes.
In CK, 9 of 36 unique proteins with signal peptides were identified as cellulases 4 , pectinases 1 , chitinases 2 , and esterases 2. For Cys, only 18 of unique proteins with signal peptides were obtained, in which one cellulase, two hemicellulases, three pectinases, nine esterases, two oxidoreductases, and one transferase were identified. Isolated mRNA was sequenced at an average depth of 60 million paired-end reads for each sample, and relative abundances in the form of RPKM reads per kilobase per million mapped reads values were calculated for each protein-coding gene.
The transcriptomes results showed high pairwise correlations Fig. The data obtained in this study also exhibited the same pattern, and the RPKM values of the proteins with supportive reliability most likely expressed on a protein level perfectly matched our data Fig.
Principal component analysis PCA was applied to reveal the relationship between different treatments, including CK, Cys, and Met, and the results showed that the differences between the various treatments were significant. Meanwhile, the biological repetitions of different treatments in both the transcriptome and proteome were ideal.
Both transcriptomic and proteomic analyses were carried out to compare the differences among different treatments, and the results indicated that genes were exclusively identified at the mRNA level, ten genes were solely found at the protein level, genes were detected at both levels, and genes were not detected Fig. It should be noted that most transcripts not identified at the protein level might be due to the low abundance of related proteins.
The proteins not detected in the transcriptome were numerous critical extracellular proteins, which demonstrated that proteomic results could contribute information not accessible at the transcript level and vice versa. Comparison of proteome and transcriptome data of A. The genes have been shown to be more likely to be translated into functional proteins; f pie chart shows the relationship between the identified proteome and the two omics proteome and transcriptome.
A total of , 21, 55, 96, 69, and 14 genes with a signal peptide were identified as members of the carbohydrate-binding modules CBM , glycoside hydrolases GH , auxiliary activities AA , carbohydrate esterases CE , glycosyl transferases GT , and polysaccharide lyases PL families, respectively, based on the genomic annotation results. The CAZyme transcripts and the proteome results demonstrated that A. RDA analysis was carried out to reveal the correlations between different proteins and various enzyme activities, as shown in Additional file 1 : Figure S5, and RDA1 and RDA2 represented a total difference of It can be seen from the plot that several highly expressed proteins red line had a good positive correlation with various enzyme activities black line.
Thus, the proteomic analysis results were highly consistent with the corresponding enzyme activity determination results. Protein—protein interaction analysis was carried out through cytoscape to reveal the relationship of various proteins involved in different metabolic pathways. The proteome—wide interaction networks of different proteins connected to the KEGG categories yellow triangles could be applied to demonstrate the expression level of different proteins and the relationship between the proteins and specific metabolic pathways Fig.
The protein node sizes indicate the expression level of different proteins, while node colors indicate the upregulation red or downregulation blue of different proteins in the form of log2 FC. Compared to CK, the proteins involved in various metabolic pathways presented different expression levels, and it was even more interesting to find that most of the proteins involved in starch and sucrose metabolism were significantly upregulated, which indicated that the addition of cysteine could improve the lignocellulose degradation capacity of Z5 Fig.
Proteome—wide expression changes on cellulose fermentation visualized as a cytoscape interaction network. Protein node sizes show protein expression absolute protein expression, APEX. Node colors are expression changes as log2-fold changes. The black dotted circles in a , b are the starch and sucrose pathways and their associated proteins.
The black arrow in a indicates the oxidative phosphorylation pathway, and the black arrow in b indicates the ribosome pathway. The ten most critical enrichment pathways were selected to compare the different metabolism of Z5 under various treatments. The results indicated that starch and sucrose metabolism increased in Cys, while decreasing sharply in Met in the proteome analysis results, which exhibited a similar trend with the results obtained in the transcriptome analysis.
The amino acid synthesis and metabolic pathways in Met were mainly enriched, whereas most of these pathways in Cys were downregulated or not changed, which occurred both in the transcriptome and proteome.
The Genome 10K Project: A Way Forward
Metrics details. As a ubiquitous filamentous fungal, Aspergillus spp. Nevertheless, the production of various extracellular enzymes can be influenced by different factors including nitrogen source, carbon source, cultivation temperature, and initial pH value. Thus, this study aims to reveal how amino acids affect the decomposition of lignocellulose by Aspergillus fumigatus Z5 through transcriptional and proteomics methods. The activities of several lignocellulosic enzymes secreted by A.
Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome
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