GWAS of lipids in Greenlanders finds association signals shared with Europeans and reveals an independent PCSK9 association signal.

Perturbation of lipid homoeostasis is a major risk factor for cardiovascular disease (CVD), the leading cause of death worldwide. We aimed to identify genetic variants affecting lipid levels, and thereby risk of CVD, in Greenlanders. Genome-wide association studies (GWAS) of six blood lipids, triglycerides, LDL-cholesterol, HDL-cholesterol, total cholesterol, as well as apolipoproteins A1 and B, were performed in up to 4473 Greenlanders. For genome-wide significant variants, we also tested for associations with additional traits, including CVD events. We identified 11 genome-wide significant loci associated with lipid traits. Most of these loci were already known in Europeans, however, we found a potential causal variant near PCSK9 (rs12117661), which was independent of the known PCSK9 loss-of-function variant (rs11491147). rs12117661 was associated with lower LDL-cholesterol (ßSD(SE) = -0.22 (0.03), p = 6.5 × 10-12) and total cholesterol (-0.17 (0.03), p = 1.1 × 10-8) in the Greenlandic study population. Similar associations were observed in Europeans from the UK Biobank, where the variant was also associated with a lower risk of CVD outcomes. Moreover, rs12117661 was a top eQTL for PCSK9 across tissues in European data from the GTEx portal, and was located in a predicted regulatory element, supporting a possible causal impact on PCSK9 expression. Combined, the 11 GWAS signals explained up to 16.3% of the variance of the lipid traits. This suggests that the genetic architecture of lipid levels in Greenlanders is different from Europeans, with fewer variants explaining the variance.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins.

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

Reconstruction of a Genome-Scale Metabolic Model of Scenedesmus obliquus and Its Application for Lipid Production under Three Trophic Modes.

Green microalgae have emerged as beneficial feedstocks for biofuel production. A systems-level understanding of the biochemical network is needed to harness the microalgal metabolic capacity for bioproduction. Genome-scale metabolic modeling (GEM) showed immense potential in rational metabolic engineering, utilizing biochemical flux distribution analysis. Here, we report the first GEM for the green microalga, Scenedesmus obliquus (iAR632), a promising biodiesel feedstock with high lipid-storing capability. iAR632 comprises 1467 reactions, 734 metabolites, and 632 genes distributed among 7 compartments. The model was optimized under three different trophic modes of microalgal cultivation, i.e., autotrophy, mixotrophy, and heterotrophy. The robustness of the reconstructed network was confirmed by analyzing its sensitivity to the biomass components. Pathway-level flux profiles were analyzed, and significant flux space expansion was noticed majorly in reactions associated with lipid biosynthesis. In agreement with the experimental observation, iAR632 predicted about 3.8-fold increased biomass and almost 4-fold higher lipid under mixotrophy than the other trophic modes. Thus, the assessment of the condition-specific metabolic flux distribution of iAR632 suggested that mixotrophy is the preferred cultivation condition for improved microalgal growth and lipid production. Overall, the reconstructed GEM and subsequent analyses will provide a systematic framework for developing model-driven strategies to improve microalgal bioproduction.

Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs.

Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry.

Most genome-wide association studies (GWAS) for lipid traits focus on the separate analysis of lipid traits. Moreover, there are limited GWASs evaluating the genetic variants associated with multiple lipid traits in African ancestry. To further identify and localize loci with pleiotropic effects on lipid traits, we conducted a genome-wide meta-analysis, multi-trait analysis of GWAS (MTAG), and multi-trait fine-mapping (flashfm) in 125,000 individuals of African ancestry. Our meta-analysis and MTAG identified four and 14 novel loci associated with lipid traits, respectively. flashfm yielded an 18% mean reduction in the 99% credible set size compared to single-trait fine-mapping with JAM. Moreover, we identified more genetic variants with a posterior probability of causality >0.9 with flashfm than with JAM. In conclusion, we identified additional novel loci associated with lipid traits, and flashfm reduced the 99% credible set size to identify causal genetic variants associated with multiple lipid traits in African ancestry.

Wounding induces suberin deposition, relevant gene expressions and changes of endogenous phytohormones in Chinese yam (Dioscorea opposita) tubers.

Wounds on Chinese yam (Dioscorea opposita ) tubers can ocurr during harvest and handling, and rapid suberisation of the wound is required to prevent pathogenic infection and desiccation. However, little is known about the causal relationship among suberin deposition, relevant gene expressions and endogenous phytohormones levels in response to wounding. In this study, the effect of wounding on phytohormones levels and the expression profiles of specific genes involved in wound-induced suberisation were determined. Wounding rapidly increased the expression levels of genes, including PAL , C4H , 4CL , POD , KCSs , FARs , CYP86A1 , CYP86B1 , GPATs , ABCGs and GELPs , which likely involved in the biosynthesis, transport and polymerisation of suberin monomers, ultimately leading to suberin deposition. Wounding induced phenolics biosynthesis and being polymerised into suberin poly(phenolics) (SPP) in advance of suberin poly(aliphatics) (SPA) accumulation. Specifically, rapid expression of genes (e.g. PAL , C4H , 4CL , POD ) associated with the biosynthesis and polymerisation of phenolics, in consistent with SPP accumulation 3days after wounding, followed by the massive accumulation of SPA and relevant gene expressions (e.g. KCSs , FARs , CYP86A1 /B1 , GPATs , ABCGs , GELPs ). Additionally, wound-induced abscisic acid (ABA) and jasmonic acid (JA) consistently correlated with suberin deposition and relevant gene expressions indicating that they might play a central role in regulating wound suberisation in yam tubers.

Dynamic lipid interactions in the plasma membrane Na+,K+-ATPase.

The function of ion-transporting Na+,K+-ATPases depends on the surrounding lipid environment in biological membranes. Two established lipid-interaction sites A and B within the transmembrane domain have been observed to induce protein activation and stabilization, respectively. In addition, lipid-mediated inhibition has been assigned to a site C, but with the exact location not experimentally confirmed. Also, possible effects on lipid interactions by disease mutants dwelling in the membrane-protein interface remain relatively uncharacterized. We simulated human Na+,K+-ATPase α1ß1FXYD homology models in E1 and E2 states in an asymmetric, multicomponent plasma membrane to determine both wild-type and disease mutant lipid-protein interactions. The simulated wild-type lipid interactions at the established sites A and B were in agreement with experimental results thereby confirming the membrane-protein model system. The less well-characterized, proposed inhibitory site C was dominated by lipids lacking inhibitory properties. Instead, two sites hosting inhibitory lipids were identified at the extracellular side and also a cytoplasmic CHL-binding site that provide putative alternative locations of Na+,K+-ATPase inhibition. Three disease mutations, Leu302Arg, Glu840Arg and Met859Arg resided in the lipid-protein interface and caused drastic changes in the lipid interactions. The simulation results show that lipid interactions to the human Na+,K+-ATPase α1ß1FXYD protein in the plasma membrane are highly state-dependent and can be disturbed by disease mutations located in the lipid interface, which can open up for new venues to understand genetic disorders.

Associations between Lipid Profiles and Graves' Orbitopathy can Be HLA-Dependent.

The risk of Graves' orbitopathy (GO) is related to the human leukocyte antigen (HLA) profile and was demonstrated to be increased in patients with elevated total cholesterol (TC) and/or low-density lipoprotein (LDL) cholesterol. We hypothesized that there were some HLA alleles that were related to both GO and TC and/or LDL levels. Therefore, the aim of the study was to compare the TC/LDL results in patients in whom GO-related HLA alleles were present to those in whom they did not occur. HLA classes were genotyped using a next-generation sequencing method in 118 patients with Graves' disease (GD), including 63 and 55 patients with and without GO, respectively. Lipid profiles were assessed at the time of the GD diagnosis. A significant correlation between the presence of GO high-risk alleles (HLA-B*37:01 and C*03:02) and higher TC/LDL levels was found. Additionally, the presence of alleles associated with non-GO GD (HLA-C*17:01 and B*08:01), as well as alleles in linkage disequilibrium with B*08:01 (i.e., HLA-DRB1*03:01 and DQB1*02:01), was correlated with lower TC levels. These results further confirm the significance of TC/LDL in the risk of GO development and provide evidence that associations between TC/LDL and GO can be HLA-dependent.

Phenotype stability and dynamics of transposable elements in a strain of the microalga Tisochrysis lutea with improved lipid traits.

Microalgal domestication is an expanding research field that aims to multiply and accelerate the potential of microalgae for various biotechnological purposes. We investigated the stability of improved lipid traits and genetic changes of a domesticated strain of the haptophyte Tisochrysis lutea, TisoS2M2, previously obtained by a mutation-selection improvement program. After 7 years of maintenance, TisoS2M2 still displayed improved lipid traits compared with the native strain, demonstrating that a mutation-selection improvement program is suitable for obtaining a domesticated strain with stable, improved phenotype over time. We identified specific genetic variations between the native and domesticated strains and focused on the dynamics of transposable elements (TEs). DNA transposons mainly caused specific TE indels of the domesticated strain TisoS2M2, and some specific TE indels may have impacted genes associated to the neutral lipid pathway. We revealed transposition events for TEs in T. lutea and discussed on the potential role of the improvement program on their activity.

Application of Adaptive Laboratory Evolution in Lipid and Terpenoid Production in Yeast and Microalgae.

Due to the complexity of metabolic and regulatory networks in microorganisms, it is difficult to obtain robust phenotypes through artificial rational design and genetic perturbation. Adaptive laboratory evolution (ALE) engineering plays an important role in the construction of stable microbial cell factories by simulating the natural evolution process and rapidly obtaining strains with stable traits through screening. This review summarizes the application of ALE technology in microbial breeding, describes the commonly used methods for ALE, and highlights the important applications of ALE technology in the production of lipids and terpenoids in yeast and microalgae. Overall, ALE technology provides a powerful tool for the construction of microbial cell factories, and it has been widely used in improving the level of target product synthesis, expanding the range of substrate utilization, and enhancing the tolerance of chassis cells. In addition, in order to improve the production of target compounds, ALE also employs environmental or nutritional stress strategies corresponding to the characteristics of different terpenoids, lipids, and strains.

The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study.

BACKGROUND: Observational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry. METHODS: We used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG). FINDINGS: We found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals ß = 1.1 (95% CI [0.411-1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR ß = 1.619 (95% CI [0.412-2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C ß = -0.164, (95% CI = [-1.329 to 1.00]; p = 0.782), and TG ß = -0.934 (CI = [-2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR ß = 1.228 (CI = [0.477-1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis ß = -1.3 ([-2.533 to -0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (ß = -0.117 (95% CI [-1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis. INTERPRETATION: In this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry. FUNDING: Wellcome (220740/Z/20/Z).

An adaptive test based on principal components for detecting multiple phenotype associations using GWAS summary data.

Extensive evidence from genome-wide association studies (GWAS) has shown that jointly analyzing multiple phenotypes can improve the power of the association test compared to the traditional single variant versus single trait approach. Here we propose an adaptive test based on principal components (ATPC) that is powerful and efficient for discovering the association between a single variant and multiple traits. Our method only needs GWAS summary statistics that are often available. We first estimate the trait correlation matrix by LD score regression. Then, based on the correlation matrix, we construct a series of test statistics that contain different numbers of principal components. The ultimate test statistic combines the P values of these principal component-based statistics by using the aggregated Cauchy association test. The analytical P-value of the test statistic can be computed quickly without the permutation process, which is the notable feature of our proposed method. The extensive simulation studies demonstrate that ATPC can control the type I error rates and have powerful and robust performance compared to several existing tests in a wide range of simulation settings. The analysis of the lipids GWAS summary data from the Global Lipids Genetics Consortium shows that ATPC identifies 230 new SNPs that are missed by the original single trait association analysis. By searching the GWAS Catalog, some SNPs and mapped genes identified by ATPC are reported to be associated with lipid traits. Through further analysis for GWAS results, we also find some Gene Ontology terms and biological pathways related to lipids.

Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Flashing lights affect the photophysiology and expression of carotenoid and lipid synthesis genes in Nannochloropsis gaditana.

Nannochloropsis gaditana is a promising microalga for biotechnology. One of the strategies to stimulate its full potential in metabolite production is exposure to flashing lights. Here, we report how N. gaditana adapts to different flashing light regimes (5, 50, and 500 Hz) by changing its cellular physiology and the relative expression of genes related to critical cellular functions. We analyzed the differential mRNA abundance of genes related to photosynthesis, nitrogen assimilation and biosynthesis of chlorophyll, carotenoids, lipids, fatty acids and starch. Analysis of photosynthetic efficiency and high mRNA abundance of photoprotection genes supported the inference that excess excitation energy provided by light absorbance during photosynthesis was produced under low frequency flashing lights and was dissipated by photopigments via the xanthophyll-cycle. Increased relative expression levels of genes related to the synthesis of carotenoids and chlorophyll confirmed the accumulation of photopigments previously observed at low frequency flashing lights. Higher differential mRNA abundance of genes related to the triacylglycerol biosynthesis were observed at lower frequency flashing lights, possibly triggered by a poor nitrogen assimilation caused by low mRNA abundance of a nitrate reductase gene. This study advances a new understanding of algal physiology and metabolism leading to improved cellular performance and metabolite production.

Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer.

Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles.

Multiplexed Single-Nucleus RNA Sequencing Using Lipid-Oligo Barcodes.

This protocol describes a robust pipeline for simultaneously analyzing multiple samples by single-nucleus (sn)RNA-seq. cDNA obtained from each single sample are labeled with the same lipid-coupled oligonucleotide barcode (10X Genomics). Nuclei from as many as 12 individual samples can be pooled together and simultaneously processed for cDNA library construction and subsequent DNA sequencing. While previous protocols using lipid-coupled oligonucleotide barcodes were optimized for analysis of samples consisting of viable cells, this protocol is optimized for analyses of quick-frozen cell samples. The protocol ensures efficient recovery of nuclei both by incorporating high sucrose buffered solutions and by including a tracking dye (trypan blue) during nuclei isolation. The protocol also describes a procedure for removing single nuclei 'artifacts' by removing cell debris prior to single nuclear fractionation. This protocol informs the use of computational tools for filtering poorly labeled nuclei and assigning sample identity using barcode unique molecular identifier (UMI) read counts percentages. The computational pipeline is applicable to either cultured or primary, fresh or frozen cells, regardless of their cell types and species. Overall, this protocol reduces batch effects and experimental costs while enhancing sample comparison. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Labeling cells with lipid oligo barcodes and generating multiplexed single-nucleus RNA-seq libraries Basic Protocol 2: Bioinformatic deconvolution of the multiplexed snRNAseq libraries.

Chimeric inheritance and crown-group acquisitions of carbon fixation genes within Chlorobiales: Origins of autotrophy in Chlorobiales and implication for geological biomarkers.

The geological record of microbial metabolisms and ecologies primarily consists of stable isotope fractionations and the diagenetic products of biogenic lipids. Carotenoid lipid biomarkers are particularly useful proxies for reconstructing this record, providing information on microbial phototroph primary productivity, redox couples, and oxygenation. The biomarkers okenane, chlorobactane, and isorenieratene are generally considered to be evidence of anoxygenic phototrophs, and provide a record that extends to 1.64 Ga. The utility of the carotenoid biomarker record may be enhanced by examining the carbon isotopic ratios in these products, which are diagnostic for specific pathways of biological carbon fixation found today within different microbial groups. However, this joint inference assumes that microbes have conserved these pathways across the duration of the preserved biomarker record. Testing this hypothesis, we performed phylogenetic analyses of the enzymes constituting the reductive tricarboxylic acid (rTCA) cycle in Chlorobiales, the group of anoxygenic phototrophic bacteria usually implicated in the deposition of chlorobactane and isorenieretane. We find phylogenetically incongruent patterns of inheritance across all enzymes, indicative of horizontal gene transfers to both stem and crown Chlorobiales from multiple potential donor lineages. This indicates that a complete rTCA cycle was independently acquired at least twice within Chlorobiales and was not present in the last common ancestor. When combined with recent molecular clock analyses, these results predict that the Mesoproterzoic lipid biomarker record diagnostic for Chlorobiales should not preserve isotopic fractionations indicative of a full rTCA cycle. Furthermore, we conclude that coupling isotopic and biomarker records is insufficient for reliably reconstructing microbial paleoecologies in the absence of a complementary and consistent phylogenomic narrative.

Increased Lipids in Chlamydomonas reinhardtii by Multiple Regulations of DOF, LACS2, and CIS1.

Microalgal lipids are essential for biofuel and dietary supplement production. Lipid engineering for higher production has been studied for years. However, due to the complexity of lipid metabolism, single-gene engineering gradually encounters bottlenecks. Multiple gene regulation is more beneficial to boosting lipid accumulation and further clarifying the complex regulatory mechanism of lipid biosynthesis in the homeostasis of lipids, carbohydrates, and protein metabolism. Here, three lipid-related genes, DOF, LACS2, and CIS, were co-regulated in Chlamydomonas reinhartii by two circles of transformation to overexpress DOF and knock down LACS2 and CIS simultaneously. With the multiple regulations of these genes, the intracellular lipids and FA content increased by 142% and 52%, respectively, compared with CC849, whereas the starch and protein contents decreased by 45% and 24%. Transcriptomic analysis showed that genes in TAG and FA biosynthesis were up-regulated, and genes in starch and protein metabolism were down-regulated. This revealed that more carbon precursor fluxes from starch and protein metabolism were redirected towards lipid synthesis pathways. These results showed that regulating genes in various metabolisms contributed to carbon flux redirection and significantly improved intracellular lipids, demonstrating the potential of multiple gene regulation strategies and providing possible candidates for lipid overproduction in microalgae.