Shi Huang

Choreography of Transcriptomes and Lipidomes of Nannochloropsis Reveals the Mechanisms of Oil Synthesis in Microalgae

To reveal the molecular mechanisms underlying lipid accumulation in microalgae, transcriptomic and lipidomic dynamics of Nannochloropsis oceanica under nitrogen-replete and nitrogen-depleted conditions were simultaneously tracked. The temporal and spatial regulation model established in this study provides a basis for the rational genetic engineering of enhanced oil production. To reveal the molecular mechanisms of oleaginousness in microalgae, transcriptomic and lipidomic dynamics of the oleaginous microalga Nannochloropsis oceanica IMET1 under nitrogen-replete (N+) and N-depleted (N-) conditions were simultaneously tracked. At the transcript level, enhanced triacylglycerol (TAG) synthesis under N- conditions primarily involved upregulation of seven putative diacylglycerol acyltransferase (DGAT) genes and downregulation of six other DGAT genes, with a simultaneous elevation of the other Kennedy pathway genes. Under N- conditions, despite downregulation of most de novo fatty acid synthesis genes, the pathways that shunt carbon precursors from protein and carbohydrate metabolic pathways into glycerolipid synthesis were stimulated at the transcript level. In particular, the genes involved in supplying carbon precursors and energy for de novo fatty acid synthesis, including those encoding components of the pyruvate dehydrogenase complex (PDHC), glycolysis, and PDHC bypass, and suites of specific transporters, were substantially upregulated under N- conditions, resulting in increased overall TAG production. Moreover, genes involved in the citric acid cycle and β-oxidation in mitochondria were greatly enhanced to utilize the carbon skeletons derived from membrane lipids and proteins to produce additional TAG or its precursors. This temporal and spatial regulation model of oil accumulation in microalgae provides a basis for improving our understanding of TAG synthesis in microalgae and will also enable more rational genetic engineering of TAG production.

Preliminary characterization of the oral microbiota of Chinese adults with and without gingivitis

BackgroundMicrobial communities inhabiting human mouth are associated with oral health and disease. Previous studies have indicated the general prevalence of adult gingivitis in China to be high. The aim of this study was to characterize in depth the oral microbiota of Chinese adults with or without gingivitis, by defining the microbial phylogenetic diversity and community-structure using highly paralleled pyrosequencing.MethodsSix non-smoking Chinese, three with and three without gingivitis (age range 21-39 years, 4 females and 2 males) were enrolled in the present cross-sectional study. Gingival parameters of inflammation and bleeding on probing were characterized by a clinician using the Mazza Gingival Index (MGI). Plaque (sampled separately from four different oral sites) and salivary samples were obtained from each subject. Sequences and relative abundance of the bacterial 16 S rDNA PCR-amplicons were determined via pyrosequencing that produced 400 bp-long reads. The sequence data were analyzed via a computational pipeline customized for human oral microbiome analyses. Furthermore, the relative abundances of selected microbial groups were validated using quantitative PCR.ResultsThe oral microbiomes from gingivitis and healthy subjects could be distinguished based on the distinct community structures of plaque microbiomes, but not the salivary microbiomes. Contributions of community members to community structure divergence were statistically accessed at the phylum, genus and species-like levels. Eight predominant taxa were found associated with gingivitis: TM7, Leptotrichia, Selenomonas, Streptococcus, Veillonella, Prevotella, Lautropia, and Haemophilus. Furthermore, 98 species-level OTUs were identified to be gingivitis-associated, which provided microbial features of gingivitis at a species resolution. Finally, for the two selected genera Streptococcus and Fusobacterium, Real-Time PCR based quantification of relative bacterial abundance validated the pyrosequencing-based results.ConclusionsThis methods study suggests that oral samples from this patient population of gingivitis can be characterized via plaque microbiome by pyrosequencing the 16 S rDNA genes. Further studies that characterize serial samples from subjects (longitudinal study design) with a larger population size may provide insight into the temporal and ecological features of oral microbial communities in clinically-defined states of gingivitis.

Prediction of Early Childhood Caries via Spatial-Temporal Variations of Oral Microbiota.

Microbiota-based prediction of chronic infections is promising yet not well established. Early childhood caries (ECC) is the most common infection in children. Here we simultaneously tracked microbiota development at plaque and saliva in 50 4-year-old preschoolers for 2 years; children either stayed healthy, transitioned into cariogenesis, or experienced caries exacerbation. Caries onset delayed microbiota development, which is otherwise correlated with aging in healthy children. Both plaque and saliva microbiota are more correlated with changes in ECC severity (dmfs) during onset than progression. By distinguishing between aging- and disease-associated taxa and exploiting the distinct microbiota dynamics between onset and progression, we developed a model, Microbial Indicators of Caries, to diagnose ECC from healthy samples with 70% accuracy and predict, with 81% accuracy, future ECC onsets for samples clinically perceived as healthy. Thus, caries onset in apparently healthy teeth can be predicted using microbiota, when appropriately de-trended for age.

Genome editing of model oleaginous microalgae Nannochloropsis spp. by CRISPR/Cas9

Microalgae are promising feedstock for biofuels yet mechanistic probing of their cellular network and industrial strain development have been hindered by lack of genome-editing tools. Nannochloropsis spp. are emerging model microalgae for scalable oil production and carbon sequestration. Here we established a CRISPR/Cas9-based precise genome-editing approach for the industrial oleaginous microalga Nannochloropsis oceanica, using nitrate reductase (NR; g7988) as example. A new screening procedure that compares between restriction enzyme-digested nested PCR (nPCR) products derived from enzyme-digested and not-digested genomic DNA of transformant pools was developed to quickly, yet reliably, detect genome-engineered mutants. Deep sequencing of nPCR products directly amplified from pooled genomic DNA revealed over an 1% proportion of 5-bp deletion mutants and a lower frequency of 12-bp deletion mutants, with both types of editing precisely located at the targeted site. The isolated mutants, in which precise deletion of five bases caused a frameshift in NR translation, grow normally under NH4 Cl but fail to grow under NaNO3 , and thus represent a valuable chassis strain for transgenic-strain development. This demonstration of CRISPR/Cas9-based genome editing in industrial microalgae opens many doors for microalgae-based biotechnological applications.

Genomic Foundation of Starch-to-Lipid Switch in Oleaginous Chlorella spp.

The versatile chlorophyta Chlorella pyrenoidosa provides genomic insights into the trophic diversity and metabolic dynamics. The ability to rapidly switch the intracellular energy storage form from starch to lipids is an advantageous trait for microalgae feedstock. To probe this mechanism, we sequenced the 56.8-Mbp genome of Chlorella pyrenoidosa FACHB-9, an industrial production strain for protein, starch, and lipids. The genome exhibits positive selection and gene family expansion in lipid and carbohydrate metabolism and genes related to cell cycle and stress response. Moreover, 10 lipid metabolism genes might be originated from bacteria via horizontal gene transfer. Transcriptomic dynamics tracked via messenger RNA sequencing over six time points during metabolic switch from starch-rich heterotrophy to lipid-rich photoautotrophy revealed that under heterotrophy, genes most strongly expressed were from the tricarboxylic acid cycle, respiratory chain, oxidative phosphorylation, gluconeogenesis, glyoxylate cycle, and amino acid metabolisms, whereas those most down-regulated were from fatty acid and oxidative pentose phosphate metabolism. The shift from heterotrophy into photoautotrophy highlights up-regulation of genes from carbon fixation, photosynthesis, fatty acid biosynthesis, the oxidative pentose phosphate pathway, and starch catabolism, which resulted in a marked redirection of metabolism, where the primary carbon source of glycine is no longer supplied to cell building blocks by the tricarboxylic acid cycle and gluconeogenesis, whereas carbon skeletons from photosynthesis and starch degradation may be directly channeled into fatty acid and protein biosynthesis. By establishing the first genetic transformation in industrial oleaginous C. pyrenoidosa, we further showed that overexpression of an NAD(H) kinase from Arabidopsis (Arabidopsis thaliana) increased cellular lipid content by 110.4%, yet without reducing growth rate. These findings provide a foundation for exploiting the metabolic switch in microalgae for improved photosynthetic production of food and fuels.

Magnetic nanoparticle-mediated isolation of functional bacteria in a complex microbial community

Although uncultured microorganisms have important roles in ecosystems, their ecophysiology in situ remains elusive owing to the difficulty of obtaining live cells from their natural habitats. In this study, we employed a novel magnetic nanoparticle-mediated isolation (MMI) method to recover metabolically active cells of a group of previously uncultured phenol degraders, Burkholderiales spp., from coking plant wastewater biosludge; five other culturable phenol degraders—Rhodococcus sp., Chryseobacterium sp. and three different Pseudomonas spp.—were also isolated from the same biosludge using traditional methods. The kinetics of phenol degradation by MMI-recovered cells (MRCs) was similar to that of the original sludge. Stable isotope probing (SIP) and pyrosequencing of the 16S rRNA from the ‘heavy’ DNA (13C-DNA) fractions indicated that Burkholderiales spp. were the key phenol degraders in situ in the biosludge, consistent with the results of MRCs. Single-cell Raman micro-spectroscopy was applied to probe individual bacteria in the MRCs obtained from the SIP experiment and showed that 79% of them were fully 13C-labelled. Biolog assays on the MRCs revealed the impact of various carbon and nitrogen substrates on the efficiency of phenol degradation in the wastewater treatment plant biosludge. Specifically, hydroxylamine, a metabolite of ammonia oxidisation, but not nitrite, nitrate or ammonia, inhibited phenol degradation in the biosludge. Our results provided a novel insight into the occasional abrupt failure events that occur in the wastewater treatment plant. This study demonstrated that MMI is a powerful tool to recover live and functional cells in situ from a complex microbial community to enable further characterisation of their physiology.

Predictive modeling of gingivitis severity and susceptibility via oral microbiota

Predictive modeling of human disease based on the microbiota holds great potential yet remains challenging. Here, 50 adults underwent controlled transitions from naturally occurring gingivitis, to healthy gingivae (baseline), and to experimental gingivitis (EG). In diseased plaque microbiota, 27 bacterial genera changed in relative abundance and functional genes including 33 flagellar biosynthesis-related groups were enriched. Plaque microbiota structure exhibited a continuous gradient along the first principal component, reflecting transition from healthy to diseased states, which correlated with Mazza Gingival Index. We identified two host types with distinct gingivitis sensitivity. Our proposed microbial indices of gingivitis classified host types with 74% reliability, and, when tested on another 41-member cohort, distinguished healthy from diseased individuals with 95% accuracy. Furthermore, the state of the microbiota in naturally occurring gingivitis predicted the microbiota state and severity of subsequent EG (but not the state of the microbiota during the healthy baseline period). Because the effect of disease is greater than interpersonal variation in plaque, in contrast to the gut, plaque microbiota may provide advantages in predictive modeling of oral diseases.

Intestinal Microbiota Distinguish Gout Patients from Healthy Humans

Current blood-based approach for gout diagnosis can be of low sensitivity and hysteretic. Here via a 68-member cohort of 33 healthy and 35 diseased individuals, we reported that the intestinal microbiota of gout patients are highly distinct from healthy individuals in both organismal and functional structures. In gout, Bacteroides caccae and Bacteroides xylanisolvens are enriched yet Faecalibacterium prausnitzii and Bifidobacterium pseudocatenulatum depleted. The established reference microbial gene catalogue for gout revealed disorder in purine degradation and butyric acid biosynthesis in gout patients. In an additional 15-member validation-group, a diagnosis model via 17 gout-associated bacteria reached 88.9% accuracy, higher than the blood-uric-acid based approach. Intestinal microbiota of gout are more similar to those of type-2 diabetes than to liver cirrhosis, whereas depletion of Faecalibacterium prausnitzii and reduced butyrate biosynthesis are shared in each of the metabolic syndromes. Thus the Microbial Index of Gout was proposed as a novel, sensitive and non-invasive strategy for diagnosing gout via fecal microbiota.

A culture-independent approach to unravel uncultured bacteria and functional genes in a complex microbial community

Most microorganisms in nature are uncultured with unknown functionality. Sequence-based metagenomics alone answers ‘who/what are there?’ but not ‘what are they doing and who is doing it and how?’. Function-based metagenomics reveals gene function but is usually limited by the specificity and sensitivity of screening strategies, especially the identification of clones whose functional gene expression has no distinguishable activity or phenotypes. A ‘biosensor-based genetic transducer’ (BGT) technique, which employs a whole-cell biosensor to quantitatively detect expression of inserted genes encoding designated functions, is able to screen for functionality of unknown genes from uncultured microorganisms. In this study, BGT was integrated with Stable isotope probing (SIP)-enabled Metagenomics to form a culture-independent SMB toolbox. The utility of this approach was demonstrated in the discovery of a novel functional gene cluster in naphthalene contaminated groundwater. Specifically, metagenomic sequencing of the 13C-DNA fraction obtained by SIP indicated that an uncultured Acidovorax sp. was the dominant key naphthalene degrader in-situ, although three culturable Pseudomonas sp. degraders were also present in the same groundwater. BGT verified the functionality of a new nag2 operon which co-existed with two other nag and two nah operons for naphthalene biodegradation in the same microbial community. Pyrosequencing analysis showed that the nag2 operon was the key functional operon in naphthalene degradation in-situ, and shared homology with both nag operons in Ralstonia sp. U2 and Polaromonas naphthalenivorans CJ2. The SMB toolbox will be useful in providing deep insights into uncultured microorganisms and unravelling their ecological roles in natural environments.

Microbial Basis of Oral Malodor Development in Humans

To better understand the microbial basis of oral malodor development in humans, we used a cross-sectional and longitudinal study design and the pyrosequencing approach to track and compare the tongue microbiota associated with oral malodor in 29 Chinese adults who underwent a consecutive three-day evaluation for the amount of H2S excreted orally. Three levels of the oral malodor state (healthy, oral malodor, and severe oral malodor) were defined based on the H2S level. Community structure of the tongue plaques was more sensitive to changes of malodor state than to interpersonal variations or differences in sampling times. Within each individual, the structure of microbiota was relatively stable, while their variations were correlated with the change in the H2S level. Severe oral malodor microbiota were the most conserved in community structure, whereas the healthy ones were relatively varied. Oral-malodor-associated bacteria were identified. The relative abundance of Leptotrichia and Prevotella was positively correlated with oral malodor severity, whereas Hemophilus and Gemella exhibited a negative relationship with oral malodor severity. Our study provides one of the first landscapes of oral microbiota changes associated with oral malodor development and reveals microbes potentially useful to the evaluation and control of oral malodor.