Co-expression networks in Chlamydomonas reveal significant rhythmicity in batch cultures and empower gene function discovery

Iron rescues glucose-mediated photosynthesis repression during lipid accumulation in the green alga Chromochloris zofingiensis

Energy status and nutrients regulate photosynthetic protein expression. The unicellular green alga Chromochloris zofingiensis switches off photosynthesis in the presence of exogenous glucose (+Glc) in a process that depends on hexokinase (HXK1). Here, we show that this response requires that cells lack sufficient iron (-Fe). Cells grown in -Fe+Glc accumulate triacylglycerol (TAG) while losing photosynthesis and thylakoid membranes. However, cells with an iron supplement (+Fe+Glc) maintain photosynthesis and thylakoids while still accumulating TAG. Proteomic analysis shows that known photosynthetic proteins are most depleted in heterotrophy, alongside hundreds of uncharacterized, conserved proteins. Photosynthesis repression is associated with enzyme and transporter regulation that redirects iron resources to (a) respiratory instead of photosynthetic complexes and (b) a ferredoxin-dependent desaturase pathway supporting TAG accumulation rather than thylakoid lipid synthesis. Combining insights from diverse organisms from green algae to vascular plants, we show how iron and trophic constraints on metabolism aid gene discovery for photosynthesis and biofuel production.

Pyroptosis-Related Genes as Diagnostic Markers in Chronic Obstructive Pulmonary Disease and Its Correlation with Immune Infiltration

Background

Chronic obstructive pulmonary disease (COPD) stands as a predominant cause of global morbidity and mortality. This study aims to elucidate the relationship between pyroptosis-related genes (PRGs) and COPD diagnosis in the context of immune infiltration, ultimately proposing a PRG-based diagnostic model for predicting COPD outcomes.

Methods

Clinical data and PRGs of COPD patients were sourced from the GEO database. The "ConsensusClusterPlus" package was employed to generate molecular subtypes derived from PRGs that were identified through differential expression analysis and LASSO Cox analysis. A diagnostic signature including eight genes (CASP4, CASP5, ELANE, GPX4, NLRP1, GSDME, NOD1and IL18) was also constructed. Immune cell infiltration calculated by the ESTIMATE score, Stroma scores and Immune scores were also compared on the basis of pyroptosis-related molecular subtypes and the risk signature. We finally used qRT - PCR to detect the expression levels of eight genes in COPD patient and normal.

Results

The diagnostic model, anchored on eight PRGs, underwent validation with an independent experimental cohort. The area under the receiver operating characteristic (ROC) curves (AUC) for the diagnostic model showcased values of 0.809, 0.765, and 0.956 for the GSE76925, GSE8545, and GSE5058 datasets, respectively. Distinct expression patterns and clinical attributes of PRGs were observed between the comparative groups, with functional analysis underscoring a disparity in immune-related functions between them.

Conclusion

In this study, we developed a potential as diagnostic biomarkers for COPD and have a significant role in modulating the immune response. Such insights pave the way for novel diagnostic and therapeutic strategies for COPD.

Fungal co-expression network analyses identify pathogen gene modules associated with host insect invasion

The broad host range fungal insect pathogen, Beauveria bassiana, has been commercialized as an alternative to chemical insecticides for pest control worldwide. B. bassiana represents a unique model system with which to examine host-pathogen interactions, and a wide range of genes and processes have been studied. However, significant aspects of virulence, particularly on the genomic scale, remain poorly studied. Here, we have combined available transcriptomes with three newly generated data sets for a combined total analysis of 76 deep-sequenced samples covering growth, development, stress responses, and infection during the life cycle of B. bassiana. Co-expression network analyses resulted in the identification of gene modules enriched during two critical stages of the infection process, namely (i) cuticle penetration and (ii) in vivo hyphal body (dimorphic transition) growth capable of avoiding innate and humoral immune defenses. These analyses identify unique signatures of metabolism, signaling, secondary metabolite production, host defense suppression, membrane reorganization, effector production, and secretion for each stage, including genetic regulators and epigenetic patterns. These data provide a comprehensive framework for understanding and probing fungal adaptations to its pathogenic life cycle and expand the candidate repertoire for continued dissection of the host-pathogen interaction. IMPORTANCE Insect fungal pathogens have evolved unique strategies for overcoming host structural and immunological defenses that span from the sclerotized cuticle to innate and humoral cellular responses. Two critical stages of the infection process involve (i) cuticle penetration and (ii) immune evasion within the insect hemocoel. A set of 76 global transcriptomic data for B. bassiana that include the cuticle penetration and hemocoel growth stages were analyzed for patterns (gene modules) of expression, yielding unique insights into these different life stages. These analyses integrate gene networks involved in fungal development, stress response and pathogenesis to further the systematic understanding of the global processes integral to the unique adaptation employed by fungal pathogens of insects.

Chlamydomonas: Fast tracking from genomics

Elucidating biological processes has relied on the establishment of model organisms, many of which offer advantageous features such as rapid axenic growth, extensive knowledge of their physiological features and gene content, and the ease with which they can be genetically manipulated. The unicellular green alga Chlamydomonas reinhardtii has been an exemplary model that has enabled many scientific breakthroughs over the decades, especially in the fields of photosynthesis, cilia function and biogenesis, and the acclimation of photosynthetic organisms to their environment. Here, we discuss recent molecular/technological advances that have been applied to C. reinhardtii and how they have further fostered its development as a "flagship" algal system. We also explore the future promise of this alga in leveraging advances in the fields of genomics, proteomics, imaging, and synthetic biology for addressing critical future biological issues.

Identification of biomarkers and immune infiltration in acute myocardial infarction and heart failure by integrated analysis

The mortality of heart failure after acute myocardial infarction (AMI) remains high. The aim of the present study was to analyze hub genes and immune infiltration in patients with AMI and heart failure (HF). The study utilized five publicly available gene expression datasets from peripheral blood in patients with AMI who either developed or did not develop HF. The unbiased patterns of 24 immune cell were estimated by xCell algorithm. Single-cell RNA sequencing data were used to examine the immune cell infiltration in heart failure patients. Hub genes were validated by quantitative reverse transcription-PCR (RT-qPCR). In comparison with the coronary heart disease (CHD) group, immune infiltration analysis of AMI patients showed that macrophages M1, macrophages, monocytes, natural killer (NK) cells, and NKT cells were the five most highly activated cell types. Five common immune-related genes (S100A12, AQP9, CSF3R, S100A9, and CD14) were identified as hub genes associated with AMI. Using RT-qPCR, we confirmed FOS, DUSP1, CXCL8, and NFKBIA as the potential biomarkers to identify AMI patients at risk of HF. The study identified several transcripts that differentiate between AMI and CHD, and between HF and non-HF patients. These findings could improve our understanding of the immune response in AMI and HF, and allow for early identification of AMI patients at risk of HF.

Zeaxanthin epoxidase is involved in the carotenoid biosynthesis and light-dependent growth of the marine alga Nannochloropsis oceanica

BACKGROUND

The marine alga Nannochloropsis oceanica, an emerging model belonging to Heterokont, is considered as a promising light-driven eukaryotic chassis for transforming carbon dioxide to various compounds including carotenoids. Nevertheless, the carotenogenic genes and their roles in the alga remain less understood and to be further explored.

RESULTS

Here, two phylogenetically distant zeaxanthin epoxidase (ZEP) genes from N. oceanica (NoZEP1 and NoZEP2) were functionally characterized. Subcellular localization experiment demonstrated that both NoZEP1 and NoZEP2 reside in the chloroplast yet with differential distribution patterns. Overexpression of NoZEP1 or NoZEP2 led to increases of violaxanthin and its downstream carotenoids at the expense of zeaxanthin in N. oceanica, with the extent of changes mediated by NoZEP1 overexpression being greater as compared to NoZEP2 overexpression. Suppression of NoZEP1 or NoZEP2, on the other hand, caused decreases of violaxanthin and its downstream carotenoids as well as increases of zeaxanthin; similarly, the extent of changes mediated by NoZEP1 suppression was larger than that by NoZEP2 suppression. Interestingly, chlorophyll a dropped following violaxanthin decrease in a well-correlated manner in response to NoZEP suppression. The thylakoid membrane lipids including monogalactosyldiacylglycerol also correlated with the violaxanthin decreases. Accordingly, NoZEP1 suppression resulted in more attenuated algal growth than NoZEP2 suppression did under either normal light or high light stage.

CONCLUSIONS

The results together support that both NoZEP1 and NoZEP2, localized in the chloroplast, have overlapping roles in epoxidating zeaxanthin to violaxanthin for the light-dependent growth, yet with NoZEP1 being more functional than NoZEP2 in N. oceanica. Our study provides implications into the understanding of carotenoid biosynthesis and future manipulation of N. oceanica for carotenoid production.

ARHGAP11A Is a Novel Prognostic and Predictive Biomarker Correlated with Immunosuppressive Microenvironment in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor and immune dysfunction is associated with ccRCC poor prognosis. The RhoGTPase-activating proteins (RhoGAPs) family was reported to affect ccRCC development, but its role in immunity and prognosis prediction for ccRCC remain unknown. In the current study, we found ARHGAP11A was the only independent risk factor among 33 RhoGAPs (hazard ratio [HR] 1.949, 95% confidence interval [CI] 1.364-2.785). High ARHGAP11A level was associated with shorter overall survival (OS, HR 2.040, 95% CI 1.646-3.417) and ARHGAP11A is a prognostic biomarker for ccRCC. ARHGAP11A knockdown suppressed renal cell carcinoma (RCC) cell proliferation, colony formation, and migration, suggesting the promoting role of ARHGAP11A on RCC development. Mechanistically, ARHGAP11A might contribute to the suppressive tumor immune microenvironment (TIME). High ARHGAP11A level was correlated with infiltration of immunosuppressive cells (including T helper 2 (Th2) cells, regulatory T (Treg) cells, myeloid derived suppressor cells (MDSC), and M2 macrophage cells), activation of immunosuppressive pathways (IL6-JAK-STAT3 signaling and IFNγ response), and expression of inhibitory immune checkpoints (ICs). ARHGAP11A could promote T cell exhaustion and induce immune escape. ccRCC patients with low ARHGAP11A level were more suitable for immune checkpoint inhibitors (ICIs) therapy, while those with high ARHGAP11A level might benefit from a combination of ARHGAP11A blockade and ICIs. In all, ARHGAP11A might serve as a novel prognostic marker, therapeutic target, and predictor in the clinical response to ICIs therapy for ccRCC.

Differential Effect of Vaginal Microbiota on Spontaneous Preterm Birth among Chinese Pregnant Women

Objective

The effect of vaginal microbiota on spontaneous preterm birth (sPTB) has not been fully addressed, and few studies have explored the associations between vaginal taxa and sPTB in the gestational diabetes mellitus (GDM) and non-GDM groups, respectively. Study Design. To minimize external interference, a total of 41 pregnant women with sPTB and 308 controls (pregnant women without sPTB) from same regain were enrolled in this case-cohort study. Controls were randomly selected at baseline. With the exception of GDM, other characteristics were not significantly different between the two groups. Vaginal swabs were collected at early second trimester. Using 16S amplicon sequencing, the main bioinformatics analysis was performed on the platform of QIIME 2. Vaginal microbiota traits of the sPTB group were compared with controls. Finally, the effects of binary taxa on sPTB in the GDM group and the non-GDM group were analyzed, respectively.

Results

The proportion of GDM in the sPTB (19.51%) was higher than the controls (7.47%, P = 0.018). The vaginal microbiota of pregnant women with sPTB exhibited higher alpha diversity metrics (observed features, P = 0.001; Faith's phylogenetic diversity, P = 0.013) and different beta diversity metrics (unweighted UniFrac, P = 0.006; Jaccard's distance, P = 0.004), compared with controls. The presence of Lactobacillus paragasseri/gasseri (aOR: 3.12, 95% CI: 1.24-7.84), Streptococcus (aOR: 3.58, 95% CI: 1.68-7.65), or Proteobacteria (aOR: 3.39, 95% CI: 1.55-7.39) was associated with an increased risk of sPTB in the non-GDM group (P < 0.05). However, the relative abundance of novel L. mulieris (a new species of the L. delbrueckii group) was associated with a decreased risk of sPTB (false discovery rate, 0.10) in all pregnant women.

Conclusion

GDM may modify the association of vaginal taxa with sPTB, suggesting that maternal GDM should be considered when using vaginal taxa to identify pregnant women at high risk of sPTB.

MMP1 acts as a potential regulator of tumor progression and dedifferentiation in papillary thyroid cancer

Papillary thyroid cancer (PTC) is one of the malignancies with an excellent prognosis. However, in PTC, progression or dedifferentiation into poorly differentiated thyroid cancer (PDTC) or anaplastic thyroid cancer (ATC) extremely jeopardizes patients’ prognosis. MMP1 is a zinc-dependent endopeptidase, and its role in PTC progression and dedifferentiation is unclear. In this study, transcriptome data of PDTC/ATC and PTC from the Gene Expression Omnibus and The Cancer Genome Atlas databases were utilized to perform an integrated analysis of MMP1 as a potential regulator of tumor progression and dedifferentiation in PTC. Both bulk and single-cell RNA-sequencing data confirmed the high expression of MMP1 in ATC tissues and cells, and further study verified that MMP1 possessed good diagnostic and prognostic value in PTC and PDTC/ATC. Up-regulated MMP1 was found to be positively related to more aggressive clinical characteristics, worse survival, extracellular matrix-related pathways, oncogenic immune microenvironment, more mutations, higher stemness, and more dedifferentiation of PTC. Meanwhile, in vitro experiments verified the high level of MMP1 in PDTC/ATC cell lines, and MMP1 knockdown and its inhibitor triolein could both inhibit the cell viability of PTC and PDTC/ATC. In conclusion, our findings suggest that MMP1 is a potential regulator of tumor progression and dedifferentiation in PTC, and might become a novel therapeutic target for PTC, especially for more aggressive PDTC and ATC.

Integrating RNA-seq and scRNA-seq to explore the biological significance of NAD + metabolism-related genes in the initial diagnosis and relapse of childhood B-cell acute lymphoblastic leukemia

BACKGROUND

Nicotinamide Adenine Dinucleotide (NAD) depletion is reported to be a potential treatment for B-cell Acute Lymphoblastic Leukemia (B-ALL), but the mechanism of NAD metabolism-related genes (NMRGs) in B-ALL relapse remains unclear.

METHODS

Transcriptome data (GSE3912), and single-cell sequencing data (GSE130116) of B-ALL patients were downloaded from Gene Expression Omnibus (GEO) database. NMRGs were sourced from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Further, the differentially expressed NMRGs (DE-NMRGs) were selected from the analysis between initial diagnosis and relapse B-ALL samples, which further performed functional enrichment analyses. The biomarkers were obtained through random forest (RF) algorithm and repeated cross validation. Additionally, cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to evaluate the immune cell differences between the initial diagnosis and relapse samples, and the correlations between biomarkers and gene markers of differential immune cells were analyzed. Furthermore, single cell RNA sequencing was conducted in the GSE130116 dataset to find key cell clusters. In addition, according to biomarkers expressions, cell clusters were categorized into high and low biomarker expression groups, and Gene Set Enrichment Analysis (GSEA) analysis was performed on them. Finally, the cell clusters with the highest expression of biomarkers were selected to explore the roles of biomarkers in different cell clusters and identify transcription factors (TFs) influencing biological markers.

RESULTS

23 DE-NMRGs were screened out, which were mainly enriched in nucleoside phosphate metabolic process, nucleotide metabolic process, and Nicotinate and nicotinamide metabolism. Moreover, 3 biomarkers (NADSYN1, SIRT3, and PARP6) were identified from the machine learning. CIBERSORT results demonstrated that four types of immune cells (B Cells naive, Monocyte, Neutrophils, and T cells CD4 memory Activated) were significantly different between the initial diagnosis and the relapse B-ALL samples, and there were strong correlations between biomarkers and differential immune cells such as positive correlation between NADSYN1 and B Cells naive. The single cell analyses showed that the biomarkers were highly expressed in common myeloid progenitors (CMP), granulocyte-macrophage progenitor (GMP), and megakaryocyte-erythroid progenitor (MEP) cell clusters. Gene set enrichment analysis (GSEA) results indicated that 55 GO terms and 3 KEGG pathways were enriched by the genes in high and low biomarker expression groups. It was found that TF CREB3L2(+) was significantly reduced in the high expression group, which may be the TF affecting biomarkers in the high expression group.

CONCLUSION

This study identified NADSYN1, SIRT3, and PARP6 as the biomarkers of B-ALL, explored biological significance of NMRGs in the initial diagnosis and relapse of B-ALL, and revealed mechanism of biomarkers at the level of the single cell.

A potential EARLY FLOWERING 3 homolog in Chlamydomonas is involved in the red/violet and blue light signaling pathways for the degradation of RHYTHM OF CHLOROPLAST 15

Light plays a major role in resetting the circadian clock, allowing the organism to synchronize with the environmental day and night cycle. In Chlamydomonas the light-induced degradation of the circadian clock protein, RHYTHM OF CHLOROPLAST 15 (ROC15), is considered one of the key events in resetting the circadian clock. Red/violet and blue light signals have been shown to reach the clock via different molecular pathways; however, many of the participating components of these pathways are yet to be elucidated. Here, we used a forward genetics approach using a reporter strain that expresses a ROC15-luciferase fusion protein. We isolated a mutant that showed impaired ROC15 degradation in response to a wide range of visible wavelengths and impaired light-induced phosphorylation of ROC15. These results suggest that the effects of different wavelengths converge before acting on ROC15 or at ROC15 phosphorylation. Furthermore, the mutant showed a weakened phase resetting in response to light, but its circadian rhythmicity remained largely unaffected under constant light and constant dark conditions. Surprisingly, the gene disrupted in this mutant was found to encode a protein that possessed a very weak similarity to the Arabidopsis thaliana EARLY FLOWERING 3 (ELF3). Our results suggest that this protein is involved in the many different light signaling pathways to the Chlamydomonas circadian clock. However, it may not influence the transcriptional oscillator of Chlamydomonas to a great extent. This study provides an opportunity to further understand the mechanisms underlying light-induced clock resetting and explore the evolution of the circadian clock architecture in Viridiplantae.

Resetting of the circadian clock is crucial for an organism, as it allows the synchronization of its internal processes with the day/night cycle. Environmental signals—such as light and temperature—contribute to this event. In plants, the molecular mechanisms underlying the light-induced resetting of the circadian clock have been well-studied in the streptophyte, Arabidopsis thaliana, and has been explored in some chlorophyte algae such as Ostreococcus tauri and Chlamydomonas reinhardtii. Here, we used a forward genetics approach to examine the light signaling pathway of a process considered critical for the light resetting of the Chlamydomonas clock—light-induced degradation of the circadian clock protein ROC15. We explored various aspects of the isolated mutant, such as the degradation of ROC15 in response to a range of visible wavelengths, the circadian rhythm, and the phase resetting of the rhythm. We show that the effects of different wavelengths of light converge before acting on ROC15 or at ROC15 phosphorylation with the aid of a potential homolog of the Arabidopsis thaliana ELF3. Our findings contradict the existing view that there is no known homolog of ELF3 in chlorophyte algae. This study, therefore, sheds light on the evolutionary aspects of the Viridiplantae circadian clocks and their light resetting.

The landscape of Chlamydomonas histone H3 lysine 4 methylation reveals both constant features and dynamic changes during the diurnal cycle

Chromatin modifications are epigenetic regulatory features with major roles in various cellular events, yet they remain understudied in algae. We interrogated the genome-wide distribution pattern of mono- and trimethylated histone H3 lysine 4 (H3K4) using chromatin-immunoprecipitation followed by deep-sequencing (ChIP-seq) during key phases of the Chlamydomonas cell cycle: early G1 phase, Zeitgeber Time 1 (ZT1), when cells initiate biomass accumulation, S/M phase (ZT13) when cells are replicating DNA and undergoing mitosis, and late G0 phase (ZT23) when they are quiescent. Tri-methylated H3K4 was predominantly enriched at transcription start sites of the majority of protein coding genes (85%). The likelihood of a gene being marked by H3K4me3 correlated with it being transcribed at some point during the life cycle but not necessarily by continuous active transcription, as exemplified by early zygotic genes, which may remain transcriptionally dormant for thousands of generations between sexual cycles. The exceptions to this rule were around 120 loci, some of which encode non-poly-adenylated transcripts, such as small nuclear RNAs and replication-dependent histones that had H3K4me3 peaks only when they were being transcribed. Mono-methylated H3K4 was the default state for the vast majority of histones that were bound outside of transcription start sites and terminator regions of genes. A small fraction of the genome that was depleted of any H3 lysine 4 methylation was enriched for DNA cytosine methylation and the genes within these DNA methylation islands were poorly expressed. Besides marking protein coding genes, H3K4me3 ChIP-seq data served also as a annotation tool for validation of hundreds of long non-coding RNA genes.

FAM171B as a Novel Biomarker Mediates Tissue Immune Microenvironment in Pulmonary Arterial Hypertension

The purpose of this study was to uncover potential diagnostic indicators of pulmonary arterial hypertension (PAH), evaluate the function of immune cells in the pathogenesis of the disease, and find innovative treatment targets and medicines with the potential to enhance prognosis. Gene Expression Omnibus was utilized to acquire the PAH datasets. We recognized differentially expressed genes (DEGs) and investigated their functions utilizing R software. Weighted gene coexpression network analysis, least absolute shrinkage and selection operators, and support vector machines were used to identify biomarkers. The extent of immune cell infiltration in the normal and PAH tissues was determined using CIBERSORT. Additionally, the association between diagnostic markers and immune cells was analyzed. In this study, 258DEGs were used to analyze the disease ontology. Most DEGs were linked with atherosclerosis, arteriosclerotic cardiovascular disease, and lung disease, including obstructive lung disease. Gene set enrichment analysis revealed that compared to normal samples, results from PAH patients were mostly associated with ECM-receptor interaction, arrhythmogenic right ventricular cardiomyopathy, the Wnt signaling pathway, and focal adhesion. FAM171B was identified as a biomarker for PAH (area under the curve = 0.873). The mechanism underlying PAH may be mediated by nave CD4 T cells, resting memory CD4 T cells, resting NK cells, monocytes, activated dendritic cells, resting mast cells, and neutrophils, according to an investigation of immune cell infiltration. FAM171B expression was also associated with resting mast cells, monocytes, and CD8 T cells. The results suggest that PAH may be closely related to FAM171B with high diagnostic performance and associated with immune cell infiltration, suggesting that FAM171B may promote the progression of PAH by stimulating immune infiltration and immune response. This study provides valuable insights into the pathogenesis and treatment of PAH.

A conserved MYB transcription factor is involved in regulating lipid metabolic pathways for oil biosynthesis in green algae

Green algae can accumulate high levels of triacylglycerol (TAG), yet knowledge remains fragmented on the regulation of lipid metabolic pathways by transcription factors (TFs). Here, via bioinformatics and in vitro and in vivo analyses, we revealed the roles of a myeloblastosis (MYB) TF in regulating TAG accumulation in green algae. CzMYB1, an R2R3-MYB from Chromochloris zofingiensis, was transcriptionally upregulated upon TAG-inducing conditions and correlated well with many genes involved in the de novo fatty acid synthesis, fatty acid activation and desaturation, membrane lipid turnover, and TAG assembly. Most promoters of these genes were transactivated by CzMYB1 in the yeast one-hybrid assay and contained the binding elements CNGTTA that were recognized by CzMYB1 through the electrophoretic mobility shift assay. CrMYB1, a close homologue of CzMYB1 from Chlamydomonas reinhardtii that recognized similar elements for binding, also transcriptionally correlated with many lipid metabolic genes. Insertional disruption of CrMYB1 severely suppressed the transcriptional expression of CrMYB1, as well as of key lipogenic genes, and impaired TAG level considerably under stress conditions. Our results reveal that this MYB, conserved in green algae, is involved in regulating global lipid metabolic pathways for TAG biosynthesis and accumulation.

Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. A total of 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO₂-concentrating mechanism and ciliogenesis. We illustrate the value of this resource by validating phenotypes and gene functions, including three new components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants; mutants in Arabidopsis thaliana genes exhibit phenotypes similar to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

Systematic phenotyping of 58,101 mutants of the model eukaryotic alga Chlamydomonas reinhardtii under 121 environmental and chemical stress conditions provides a large resource for characterizing gene function.

Comparative Phenotyping of Two Commonly Used Chlamydomonas reinhardtii Background Strains: CC-1690 (21gr) and CC-5325 (The CLiP Mutant Library Background)

The unicellular green alga Chlamydomonas reinhardtii is an excellent model organism to investigate many essential cellular processes in photosynthetic eukaryotes. Two commonly used background strains of Chlamydomonas are CC-1690 and CC-5325. CC-1690, also called 21gr, has been used for the Chlamydomonas genome project and several transcriptome analyses. CC-5325 is the background strain for the Chlamydomonas Library Project (CLiP). Photosynthetic performance in CC-5325 has not been evaluated in comparison with CC-1690. Additionally, CC-5325 is often considered to be cell-wall deficient, although detailed analysis is missing. The circadian rhythms in CC-5325 are also unclear. To fill these knowledge gaps and facilitate the use of the CLiP mutant library for various screens, we performed phenotypic comparisons between CC-1690 and CC-5325. Our results showed that CC-5325 grew faster heterotrophically in dark and equally well in mixotrophic liquid medium as compared to CC-1690. CC-5325 had lower photosynthetic efficiency and was more heat-sensitive than CC-1690. Furthermore, CC-5325 had an intact cell wall which had comparable integrity to that in CC-1690 but appeared to have reduced thickness. Additionally, CC-5325 could perform phototaxis, but could not maintain a sustained circadian rhythm of phototaxis as CC1690 did. Finally, in comparison to CC-1690, CC-5325 had longer cilia in the medium with acetate but slower swimming speed in the medium without nitrogen and acetate. Our results will be useful for researchers in the Chlamydomonas community to choose suitable background strains for mutant analysis and employ the CLiP mutant library for genome-wide mutant screens under appropriate conditions, especially in the areas of photosynthesis, thermotolerance, cell wall, and circadian rhythms.

SPINK2 is a prognostic biomarker related to immune infiltration in acute myeloid leukemia

BACKGROUND

Serine peptidase inhibitor Kazal type 2 (SPINK2) has been reported to be involved in certain cancers. We conducted an in-depth investigation on the role and mechanism of SPINK2 in acute myeloid leukemia (AML).

METHODS

The relationship between SPINK2 expression and AML clinicopathologic characteristics was determined using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Concomitantly, we used Kaplan-Meier survival analysis, as well as univariate and multivariate regression analyses to evaluate SPINK2 as a prognostic marker of AML. Additionally, we annotated the enrichment and function of SPINK2 using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Sets Enrichment Analysis (GSEA). The CIBERSORT algorithm was used to analyze the relationship between SPINK2 expression and immune infiltration.

RESULTS

SPINK2 expression was significantly higher in AML patients compared to healthy individuals (P<0.001). The area under receiver operating characteristic curve in the GSE9476 dataset was 0.660, whereas that in the Genotype-Tissue Expression (GTEx) and TCGA datasets was 0.935. In addition, GSEA also showed that several pathways were enriched in the group with high SPINK2 expression, such as PI3K-AKT signaling, PD-L1 expression, and checkpoint pathways. Analysis of immune infiltration showed that SPINK2 expression was correlated with certain immune infiltrating cells. Cox multivariate analysis revealed that the level of SPINK2 was an independent risk factor for the progression of AML (P<0.001). Moreover, age, M1, M5, M6, and CytoRisk-Poor also affected the progression of AML (P<0.05). The C-index of the nomogram in our internal validation was 0.702.

CONCLUSION

The high expression of SPINK2 in AML suggests that SPINK2 may play an important role in the immune microenvironment and thus could be a biomarker for diagnosis and prognosis of AML.

Discovery of photosynthesis genes through whole-genome sequencing of acetate-requiring mutants of Chlamydomonas reinhardtii

Large-scale mutant libraries have been indispensable for genetic studies, and the development of next-generation genome sequencing technologies has greatly advanced efforts to analyze mutants. In this work, we sequenced the genomes of 660 Chlamydomonas reinhardtii acetate-requiring mutants, part of a larger photosynthesis mutant collection previously generated by insertional mutagenesis with a linearized plasmid. We identified 554 insertion events from 509 mutants by mapping the plasmid insertion sites through paired-end sequences, in which one end aligned to the plasmid and the other to a chromosomal location. Nearly all (96%) of the events were associated with deletions, duplications, or more complex rearrangements of genomic DNA at the sites of plasmid insertion, and together with deletions that were unassociated with a plasmid insertion, 1470 genes were identified to be affected. Functional annotations of these genes were enriched in those related to photosynthesis, signaling, and tetrapyrrole synthesis as would be expected from a library enriched for photosynthesis mutants. Systematic manual analysis of the disrupted genes for each mutant generated a list of 253 higher-confidence candidate photosynthesis genes, and we experimentally validated two genes that are essential for photoautotrophic growth, CrLPA3 and CrPSBP4. The inventory of candidate genes includes 53 genes from a phylogenomically defined set of conserved genes in green algae and plants. Altogether, 70 candidate genes encode proteins with previously characterized functions in photosynthesis in Chlamydomonas, land plants, and/or cyanobacteria; 14 genes encode proteins previously shown to have functions unrelated to photosynthesis. Among the remaining 169 uncharacterized genes, 38 genes encode proteins without any functional annotation, signifying that our results connect a function related to photosynthesis to these previously unknown proteins. This mutant library, with genome sequences that reveal the molecular extent of the chromosomal lesions and resulting higher-confidence candidate genes, will aid in advancing gene discovery and protein functional analysis in photosynthesis.

Transcription Factor-Based Genetic Engineering in Microalgae

Sequence-specific DNA-binding transcription factors (TFs) are key components of gene regulatory networks. Advances in high-throughput sequencing have facilitated the rapid acquisition of whole genome assembly and TF repertoires in microalgal species. In this review, we summarize recent advances in gene discovery and functional analyses, especially for transcription factors in microalgal species. Specifically, we provide examples of the genome-scale identification of transcription factors in genome-sequenced microalgal species and showcase their application in the discovery of regulators involved in various cellular functions. Herein, we highlight TF-based genetic engineering as a promising framework for designing microalgal strains for microalgal-based bioproduction.

Single-cell RNA sequencing of batch Chlamydomonas cultures reveals heterogeneity in their diurnal cycle phase

The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of its ease of culture in the laboratory. Genomic and systems biology approaches have previously described transcriptome responses to environmental changes using bulk data, thus representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing by the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample natural algal communities. Second, scRNA-seq successfully separated single cells into nonoverlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest photosynthesis and cell division to economize resources. Notably, these groups of cells not only recapitulated known patterns observed with bulk RNA-seq but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We document experimentally that bulk RNA-seq data represent an average of typically hidden heterogeneity in the population.