Article Cite This: J. Agric. Food Chem. 2018, 66, 9147−9157
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Integrated Transcriptome and Proteome Studies Reveal the Underlying Mechanisms for Sterol Catabolism and Steroid Production in Mycobacterium neoaurum Min Liu, Liang-Bin Xiong, Xinyi Tao, Qing-Hai Liu, Feng-Qing Wang,* and Dong-Zhi Wei* State Key Laboratory of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, Shanghai 200237, People’s Republic of China J. Agric. Food Chem. 2018.66:9147-9157. Downloaded from pubs.acs.org by UNIV OF SOUTH DAKOTA on 08/29/18. For personal use only.
S Supporting Information *
ABSTRACT: Integrated transcriptome and proteome studies were performed to investigate sterol biotransformation in wildtype Mycobacterium neoaurum ATCC 25795 (Mn) and the mutant strains producing steroid intermediates. Transcriptome and proteome studies indicated that several metabolic activities were noticeably dynamic, including cholesterol degradation, central carbon metabolism, cell envelope biosynthesis, glycerol metabolism, and transport. Interestingly, a poor overall correlation between mRNA and translation profiles was found, which might contribute to the metabolic adaptation in cholesterol catabolism. A gene cluster covering 111 genes was discovered to encode for cholesterol catabolism in Mn. Generally, transcription and/or translation of the genes in KstR1 regulon was upregulated, and the induction of genes in KstR2 regulon was not as significant as that of KstR1 regulon. Several induced genes showing potential roles for cholesterol catabolism were found. Further identification of these genes and investigation of the correlation among key metabolic activities could help for the development of efficient steroid-producing strains. KEYWORDS: sterol catabolism, transcriptome, proteome, Mycobacterium
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INTRODUCTION Natural sterol compounds play important roles in the maintenance of proper membrane permeability and fluidity and cell differentiation and proliferation.1,2 The bacterial catabolism of sterol has attracted considerable attention because of the relevance with pathogenesis in pathogenic strains and the potential application for steroid synthesis in non-pathogenic strains.3−5 Steroid pharmaceuticals are the second largest medical category next to antibiotics. Sterol bioconversion has achieved considerable progress as a result of an excellent work, which has disclosed a gene cluster encoding for the catabolism of cholesterol in Mycobacterium tuberculosis (Mtb) and Rhodococcus strain RHA1.6 Along with the advances in genetic and metabolic engineering, Mycobacterium neoaurum (Mn), an efficient sterol consumer, has been engineered to produce valuable steroid intermediates, which are key precursors for the steroid hormones.7−10 At present, important C19 and C22 steroid intermediates have been achieved from sterol metabolism.11 C19 steroids are widely used to produce sex and adrenocortical hormones, while C22 steroids are valuable precursors for the synthesis of adrenocortical and progestational hormone in industry.3,12,13 Cholesterol catabolism is imperative for the maintenance of Mtb cells in the hosts, which has been validated experimentally to be required for the pathogenesis and virulence.14,15 Generally, uptake of sterol, degradation of the aliphatic side chain at C17, and oxidation of the steroid nucleus are major processes for cholesterol catabolism in mycobacteria.7,8 The genes for sterol catabolism were found to be within an 83 gene cluster in Mtb, which was referred to as the “Cho region” and © 2018 American Chemical Society
regulated by the TetR family transcriptional regulators (KstR1 and KstR2).14,16−18 Many genes for steroid catabolism have yet to be identified, and many of the pathway enzymes are poorly characterized. Despite the functional importance of Mycobacterium for the production of steroid intermediates, to our limited knowledge, a systematic understanding of the molecular mechanism and dynamics for sterol catabolism and steroid accumulation in Mycobacterium still remains elusive.3 Different omic studies can be integrated to capture a multilayered picture of the molecular mechanism and dynamics in a perturbed system.19,20 To deepen our understand of the underlying mechanisms of Mn to the in vitro and in vivo environment during growth on cholesterol and accumulation of valuable steroid intermediates, integrated genome, transcriptome, and proteome studies were performed to characterize the differences between wild-type Mn and various mutant Mn strains for steroid accumulation. A total of five strains were investigated, including wild-type Mn ATCC 25795 cultured without (called Mn-C) and with (called Mn-CC) cholesterol addition and mutant Mn strains producing 9α-hydroxyandrost-4-ene-3,17-dione (9OHAD, called Mn9OHAD), androst-1,4-dien-3,17-dione (ADD, called MnADD), and 22-hydroxy-23,24-bisnorchol-1,4-dien-3-one (1,4HBC, Mn-HBC, called BNA in our previous work19). To explore the differential expression of genes, four comparable groups were analyzed, including the wild-type Mn with versus Received: Revised: Accepted: Published: 9147
May 28, 2018 July 30, 2018 August 3, 2018 August 3, 2018 DOI: 10.1021/acs.jafc.8b02714 J. Agric. Food Chem. 2018, 66, 9147−9157
Article
Journal of Agricultural and Food Chemistry
Figure 1. (A) Circular chromosome map of Mn ATCC 25795 and (B) GO enrichment analysis of the genes with predicted function. The innermost skew shows G + C content distribution on 200 bp step length and the GC-skew value (green/purple). The GC content below average of the strain is shown as pea green. Amaranth means that it is above average. The outermost ring is the chromosome of Mn ATCC 25795. GO is comprised by three terms of biological process, cellular component, and molecular function. MYC/01 medium. As a control, strain Mn-C was fermented in MYC/ 02 medium by adding 10.0 g/L glucose to replace glycerol (without cholesterol addition) in MYC/01. The samples were taken at 48 h after fermentation. Two biological replicates were sequenced and analyzed for each sample. Two parts were separated from each sample for transcriptome and proteome analyses. Construction of Steroid-Producing Strains. All plasmids, primers, and strains used herein are listed in Table S1 of the Supporting Information. On the basis of a suicide plasmid of p2NIL, unmarked in-frame gene knockout was conducted, which was combined with a selectable marker cassette from pGOAL19, as
without cholesterol addition (called Mn-CC/C) and the steroid-producing strains versus Mn-CC (called Mn9OHAD/CC, Mn-ADD/CC, and Mn-HBC/CC).
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MATERIALS AND METHODS
Strains and Culture Conditions. Mycobacteria strains were aerobically cultured in MYC/01 medium at 30 °C (200 rpm), as described previously.19 For sterol biotransformation, Mn-CC and steroid-producing strains were fermented in MYC/02 medium by adding 0.5 g/L cholesterol and 10.0 g/L glucose to replace glycerol in 9148
DOI: 10.1021/acs.jafc.8b02714 J. Agric. Food Chem. 2018, 66, 9147−9157
Article
Journal of Agricultural and Food Chemistry
Figure 2. Proposed schematic diagram of cholesterol catabolism and steroid accumulation in Mn. Dashed frames indicate the three identified reticular metabolic circuit loops between the cholesterol side-chain degradation and cholesterol ring degradation. The abbreviations in blue, red, and green represent the key enzymes that determine product selectivity. KstD, 3-ketosteroid-Δ1-dehydrogenases; KSH, 3-ketosteroid-9αhydroxylases; and Hsd4A, a short-chain dehydrogenase. °C, 1 h) and then alkylated with iodoacetamide (IAM, 55 mM, darkroom, 1 h). The protein mixtures were precipitated using chilled acetone and then dissolved in 0.5 M triethylammonium bicarbonate (TEAB) for sonication (15 min, 4 °C). A total of 100 μg of protein of each sample was digested with Trypsin Gold (Promega, Madison, WI, U.S.A.) with a ratio of 20:1 (protein/trypsin, 37 °C, 4 h). The trypsin digestion was repeated again for another 8 h with the same ratio, after which peptides were dried by vacuum centrifugation. Peptides were redissolved in 0.5 M TEAB and labeled with isobaric tags as follows: Mn-C, 113; Mn-CC, 115; Mn-9OHAD, 116; Mn-ADD, 117; and Mn-HBC, 119. The labeled peptides were mixed for SCX chromatography using LC-20AB high-performance liquid chromatography (HPLC, Shimadzu, Japan) according to the protocol of the manufacturer. Dried peptides were resuspended and centrifuged at 20000g for 10 min to remove the insoluble materials. The supernatant (5 μL, about 2.5 μg) of each sample was loaded onto LC-20AD nano HPLC (C18 trap column, Shimadzu, Japan) and was then eluted onto an analytical C18 column packed in-house for separation. Data acquisition was conducted using the TripleTOF 5600 system (AB SCI EX, Concord, Ontario, Canada). The median ratio in Mascot was used to weigh and normalize the quantitative protein ratios. The ratio with p value of 1.2 was considered as significant. The iTRAQ data were submitted to PRIDE Archive with a submission number of 272271. Quantitative Reverse-Transcriptase Polymerase Chain Reaction (qRT-PCR). qRT-PCR analysis was performed using a qRTPCR (TER010-2) kit (Dingguo, Beijing, China) on the StepOne Real-Time PCR system (Applied Biosystems). After the DNA was removed, total RNA was mixed with 10× fast RT buffer (2 μL), FQRT primer mix (2 μL), RT enzyme mix (1 μL), and RNase-free double-distilled water (ddH2O, 15 μL) for preparation of cDNA
described previously.11 Strains Mn-9OHAD, Mn-ADD, and Mn-HBC were engineered by the deletion of genes kstd1, kshA1, and kshA1 and hsd4A, respectively.3,11 Thin-Layer Chromatography (TLC) Analysis. The acetic ether extraction liquid was spread on aluminum-backed silica gel 60precoated plate F254 (Merck, Germany) in petroleum ether/ethyl acetate (6:4, v/v). TLC plates were revealed by spraying with H2SO4/ H2O (1:9, v/v) and heating at 110 °C for 6 min. RNA Extraction, Sequencing, and Transcriptome Analyses. The total RNA was extracted using a FastRNA Pro Blue Kit (MP Biomedicals, Irvine, CA, U.S.A.). RNA sequencing was conducted with Illumina Hiseq 2000. Clean reads were mapped to the reference genome of Mn ATCC 2579511 by SOAPaligner/soap2. The read number was transformed into reads per kilobases per million reads (RPKM). The differently expressed genes were identified using DEGseq package in the MA-plot-based method with the random sampling model. The threshold of the false discovery rate (FDR) of ≤0.05, log2 ratio of >1 or < −1, and p value of
