Bioprospecting Plant Growth-Promoting Rhizobacteria That Mitigate Drought Stress in Grasses

This study reports the application of a novel bioprospecting procedure designed to screen plant growth-promoting rhizobacteria (PGPR) capable of rapidly colonizing the rhizosphere and mitigating drought stress in multiple hosts. Two PGPR strains were isolated by this bioprospecting screening assay and identified as Bacillus sp. (12D6) and Enterobacter sp. (16i). When inoculated into the rhizospheres of wheat (Triticum aestivum) and maize (Zea mays) seedlings, these PGPR resulted in delays in the onset of plant drought symptoms. The plant phenotype responding to drought stress was associated with alterations in root system architecture. In wheat, both PGPR isolates significantly increased root branching, and Bacillus sp. (12D6), in particular, increased root length, when compared to the control. In maize, both PGPR isolates significantly increased root length, root surface area and number of tips when compared to the control. Enterobacter sp. (16i) exhibited greater effects in root length, diameter and branching when compared to Bacillus sp. (12D6) or the control. In vitro phytohormone profiling of PGPR pellets and filtrates using LC/MS demonstrated that both PGPR strains produced and excreted indole-3-acetic acid (IAA) and salicylic acid (SA) when compared to other phytohormones. The positive effects of PGPR inoculation occurred concurrently with the onset of water deficit, demonstrating the potential of the PGPR identified from this bioprospecting pipeline for use in crop production systems under drought stress.

Host-mediated microbiome engineering (HMME) of drought tolerance in the wheat rhizosphere

Host-mediated microbiome engineering (HMME) is a strategy that utilizes the host phenotype to indirectly select microbiomes though cyclic differentiation and propagation. In this experiment, the host phenotype of delayed onset of seedling water deficit stress symptoms was used to infer beneficial microbiome-host interactions over multiple generations. By utilizing a host-centric selection approach, microbiota are selected at a community level, therein using artificial selection to alter microbiomes through both ecological and evolutionary processes. After six rounds of artificial selection using host-mediated microbiome engineering (HMME), a microbial community was selected that mediated a 5-day delay in the onset of drought symptoms in wheat seedlings. Seedlings grown in potting medium inoculated with the engineered rhizosphere from the 6th round of HMME produced significantly more biomass and root system length, dry weight, and surface area than plants grown in medium similarly mixed with autoclaved inoculum (negative control). The effect on plant water stress tolerance conferred by the inoculum was transferable at subsequent 10-fold and 100-fold dilutions in fresh non-autoclaved medium but was lost at 1000-fold dilution and was completely abolished by autoclaving, indicating the plant phenotype is mediated by microbial population dynamics. The results from 16S rRNA amplicon sequencing of the rhizosphere microbiomes at rounds 0, 3, and 6 revealed taxonomic increases in proteobacteria at the phylum level and betaproteobacteria at the class level. There were significant decreases in alpha diversity in round 6, divergence in speciation with beta diversity between round 0 and 6, and changes in overall community composition. This study demonstrates the potential of using the host as a selective marker to engineer microbiomes that mediate changes in the rhizosphere environment that improve plant adaptation to drought stress.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

De novo identification of microbial contaminants in low microbial biomass microbiomes with Squeegee

Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low-biomass environments. Contamination from DNA extraction kits or sampling lab environments leaves taxonomic "bread crumbs" across multiple distinct sample types. Here we describe Squeegee, a de novo contamination detection tool that is based upon this principle, allowing the detection of microbial contaminants when negative controls are unavailable. On the low-biomass samples, we compare Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers putative contaminants. We analyze samples of varying biomass from the Human Microbiome Project and identify likely, previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision and thus represents a computational approach for contaminant detection when negative controls are unavailable.

SARS-CoV-2 niches in human placenta revealed by spatial transcriptomics

BACKGROUND

Functional placental niches are presumed to spatially separate maternal-fetal antigens and restrict the vertical transmission of pathogens. We hypothesized a high-resolution map of placental transcription could provide direct evidence for niche microenvironments with unique functions and transcription profiles.

METHODS

We utilized Visium Spatial Transcriptomics paired with H&E staining to generate 17,927 spatial transcriptomes. By integrating these spatial transcriptomes with 273,944 placental single-cell and single-nuclei transcriptomes, we generated an atlas composed of at least 22 subpopulations in the maternal decidua, fetal chorionic villi, and chorioamniotic membranes.

FINDINGS

Comparisons of placentae from uninfected healthy controls (n = 4) with COVID-19 asymptomatic (n = 4) and symptomatic (n = 5) infected participants demonstrated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in syncytiotrophoblasts occurred in both the presence and the absence of maternal clinical disease. With spatial transcriptomics, we found that the limit of detection for SARS-CoV-2 was 1/7,000 cells, and placental niches without detectable viral transcripts were unperturbed. In contrast, niches with high SARS-CoV-2 transcript levels were associated with significant upregulation in pro-inflammatory cytokines and interferon-stimulated genes, altered metallopeptidase signaling (TIMP1), with coordinated shifts in macrophage polarization, histiocytic intervillositis, and perivillous fibrin deposition. Fetal sex differences in gene expression responses to SARS-CoV-2 were limited, with confirmed mapping limited to the maternal decidua in males.

CONCLUSIONS

High-resolution placental transcriptomics with spatial resolution revealed dynamic responses to SARS-CoV-2 in coordinate microenvironments in the absence and presence of clinically evident disease.

FUNDING

This work was supported by the NIH (R01HD091731 and T32-HD098069), NSF (2208903), the Burroughs Welcome Fund and the March of Dimes Preterm Birth Research Initiatives, and a Career Development Award from the American Society of Gene and Cell Therapy.

The impact of response to iron therapy on maternal and neonatal outcomes among pregnant women with anemia

BACKGROUND

Anemia during pregnancy is associated with increased risks of preterm birth, preeclampsia, cesarean delivery, and maternal morbidity. The most prevalent modifiable cause of pregnancy-associated anemia is iron deficiency. However, it is still unclear whether iron therapy can reduce the risks of adverse outcomes in women with anemia.

OBJECTIVE

This study aimed to determine whether response to iron therapy among women with anemia is associated with a change in odds of adverse maternal and neonatal outcomes.

STUDY DESIGN

This was a population-based cohort study (2011-2019) using an institutional database composed of obstetrical patients from 2 delivery hospitals. Patients with adequate prenatal care were classified as being anemic or nonanemic (reference). Patients with anemia were further stratified by success or failure of treatment with oral iron therapy using the American College of Obstetricians and Gynecologists criteria for anemia at the time of admission for delivery: successfully treated (Hgb≥11 g/dL) or unsuccessfully treated ("refractory;" Hgb<11 g/dL). All categories of women with anemia categories were compared with the reference group of women without anemia using chi-square and logistic regression analyses. The primary outcomes were preterm birth and preeclampsia.

RESULTS

Among the 20,690 women observed, 7416 (35.8%) were anemic. Among women with anemia, 1319 (17.8%) were refractory to iron therapy, 2695 (36.3%) had a successful response to therapy, and 3402 (45.9%) were untreated. Successfully treated patients with anemia had a significant reduction in the odds of preterm birth (5.1% vs 8.3%; adjusted odds ratio, 0.59; 95% confidence interval, 0.47-0.72) and preeclampsia (5.9% vs 8.3%; adjusted odds ratio, 0.75; 95% confidence interval, 0.61-0.91). Refractory and untreated patients had significantly increased odds of preterm birth (adjusted odds ratio, 1.44 [95% confidence interval, 1.16-1.76] and 1.45 [95% confidence interval, 1.26-1.67], respectively) and preeclampsia (adjusted odds ratio, 1.54 [95% confidence interval, 1.24-1.89] and 1.44 [95% confidence interval, 1.25-1.67], respectively). All groups of women with anemia had increased odds of postpartum hemorrhage and decreased odds of delivering a small for gestational age neonate. There was no difference in composite neonatal morbidity.

CONCLUSION

Successful treatment of anemia with oral iron therapy was associated with a reduction in the odds of preterm birth and preeclampsia. Women with refractory anemia had similar outcomes to those who were untreated, emphasizing the importance of monitoring response to iron therapy during pregnancy.

Zika virus co-opts microRNA networks to persist in placental niches detected by spatial transcriptomics

BACKGROUND

Zika virus congenital infection evades double-stranded RNA detection and may persist in the placenta for the duration of pregnancy without accompanying overt histopathologic inflammation. Understanding how viruses can persist and replicate in the placenta without causing overt cellular or tissue damage is fundamental to deciphering mechanisms of maternal-fetal vertical transmission.

OBJECTIVE

Placenta-specific microRNAs are believed to be a tenet of viral resistance at the maternal-fetal interface. We aimed to test the hypothesis that the Zika virus functionally disrupts placental microRNAs, enabling viral persistence and fetal pathogenesis.

STUDY DESIGN

To test this hypothesis, we used orthogonal approaches in human and murine experimental models. In primary human trophoblast cultures (n=5 donor placentae), we performed Argonaute high-throughput sequencing ultraviolet-crosslinking and immunoprecipitation to identify any significant alterations in the functional loading of microRNAs and their targets onto the RNA-induced silencing complex. Trophoblasts from same-donors were split and infected with a contemporary first-passage Zika virus strain HN16 (multiplicity of infection=1 plaque forming unit per cell) or mock infected. To functionally cross-validate microRNA-messenger RNA interactions, we compared our Argonaute high-throughput sequencing ultraviolet-crosslinking and immunoprecipitation results with an independent analysis of published bulk RNA-sequencing data from human placental disk specimens (n=3 subjects; Zika virus positive in first, second, or third trimester, CD45- cells sorted by flow cytometry) and compared it with uninfected controls (n=2 subjects). To investigate the importance of these microRNA and RNA interference networks in Zika virus pathogenesis, we used a gnotobiotic mouse model uniquely susceptible to the Zika virus. We evaluated if small-molecule enhancement of microRNA and RNA interference pathways with enoxacin influenced Zika virus pathogenesis (n=20 dams total yielding 187 fetal specimens). Lastly, placentae (n=14 total) from this mouse model were analyzed with Visium spatial transcriptomics (9743 spatial transcriptomes) to identify potential Zika virus-associated alterations in immune microenvironments.

RESULTS

We found that Zika virus infection of primary human trophoblast cells led to an unexpected disruption of placental microRNA regulation networks. When compared with uninfected controls, Zika virus-infected placentae had significantly altered SLC12A8, SDK1, and VLDLR RNA-induced silencing complex loading and transcript levels (-22; adjusted P value <.05; Wald-test with false discovery rate correction q<0.05). In silico microRNA target analyses revealed that 26 of 119 transcripts (22%) in the transforming growth factor-β signaling pathway were targeted by microRNAs that were found to be dysregulated following Zika virus infection in trophoblasts. In gnotobiotic mice, relative to mock controls, Zika virus-associated fetal pathogenesis included fetal growth restriction (P=.036) and viral persistence in placental tissue (P=.011). Moreover, spatial transcriptomics of murine placentae revealed that Zika virus-specific placental niches were defined by significant up-regulation of complement cascade components and coordinated changes in transforming growth factor-β gene expression. Finally, treatment of Zika virus-infected mice with enoxacin abolished placental Zika virus persistence, rescued the associated fetal growth restriction, and the Zika virus-associated transcriptional changes in placental immune microenvironments were no longer observed.

CONCLUSION

These results collectively suggest that (1) Zika virus infection and persistence is associated with functionally perturbed microRNA and RNA interference pathways specifically related to immune regulation in placental microenvironments and (2) enhancement of placental microRNA and RNA interference pathways in mice rescued Zika virus-associated pathogenesis, specifically persistence of viral transcripts in placental microenvironments and fetal growth restriction.

The third international hackathon for applying insights into large-scale genomic composition to use cases in a wide range of organisms

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.

Maternal loss-of-function of Nlrp2 results in failure of epigenetic reprogramming in mouse oocytes

Background

NLRP2 belongs to the subcortical maternal complex (SCMC) of mammalian oocytes and preimplantation embryos. This multiprotein complex, encoded by maternal-effect genes, plays a pivotal role in the zygote-to-embryo transition, early embryogenesis, and epigenetic (re)programming. The maternal inactivation of genes encoding SCMC proteins has been linked to infertility and subfertility in mice and humans. However, the underlying molecular mechanisms for the diverse functions of the SCMC, particularly how this cytoplasmic structure influences DNA methylation, which is a nuclear process, are not fully understood.

Results

We undertook joint transcriptome and DNA methylome profiling of pre-ovulatory germinal-vesicle oocytes from Nlrp2-null, heterozygous (Het), and wild-type (WT) female mice. We identified numerous differentially expressed genes (DEGs) in Het and Nlrp2-null when compared to WT oocytes. The genes for several crucial factors involved in oocyte transcriptome modulation and epigenetic reprogramming, such as DNMT1, UHRF1, KDM1B and ZFP57 were overexpressed in Het and Nlrp2-null oocytes. Absence or reduction of Nlrp2, did not alter the distinctive global DNA methylation landscape of oocytes, including the bimodal pattern of the oocyte methylome. Additionally, although the methylation profile of germline differentially methylated regions (gDMRs) of imprinted genes was preserved in oocytes of Het and Nlrp2-null mice, we found altered methylation in oocytes of both genotypes at a small percentage of the oocyte-characteristic hyper- and hypomethylated domains. Through a tiling approach, we identified specific DNA methylation differences between the genotypes, with approximately 1.3% of examined tiles exhibiting differential methylation in Het and Nlrp2-null compared to WT oocytes.

Conclusions

Surprisingly, considering the well-known correlation between transcription and DNA methylation in developing oocytes, we observed no correlation between gene expression differences and gene-body DNA methylation differences in Nlrp2-null versus WT oocytes or Het versus WT oocytes. We therefore conclude that post-transcriptional changes in the stability of transcripts rather than altered transcription is primarily responsible for transcriptome differences in Nlrp2-null and Het oocytes.

Microbial determinants of dementia risk in subjects of Mexican descent with type 2 diabetes living in South Texas

Type 2 diabetes (T2D) is a common forerunner of neurodegeneration and dementia, including Alzheimer's Disease (AD), yet the underlying mechanisms remain unresolved. Individuals of Mexican descent living in South Texas have increased prevalence of comorbid T2D and early onset AD, despite low incidence of the predisposing APOE-e4 variant and an absence of the phenotype among relatives residing in Mexico - suggesting a role for environmental factors in coincident T2D and AD susceptibility. Here, in a small clinical trial, we show dysbiosis of the human gut microbiome could contribute to neuroinflammation and risk for AD in this population. Divergent Gastrointestinal Symptom Rating Scale (GSRS) responses, despite no differences in expressed dietary preferences, provided the first evidence for altered gut microbial ecology among T2D subjects (sT2D) versus population-matched healthy controls (HC). Metataxonomic 16S rRNA sequencing of participant stool revealed a decrease in alpha diversity of sT2D versus HC gut communities and identified BMI as a driver of gut community structure. Linear discriminant analysis effect size (LEfSe) identified a significant decrease in the relative abundance of the short-chain fatty acid-producing taxa Lachnospiraceae, Faecalibacterium, and Alistipes and an increase in pathobionts Escherichia-Shigella, Enterobacter, and Clostridia innocuum among sT2D gut microbiota, as well as differentially abundant gene and metabolic pathways. These results suggest characterization of the gut microbiome of individuals with T2D could identify key actors among "disease state" microbiota which may increase risk for or accelerate the onset of neurodegeneration. Furthermore, they identify candidate microbiome-targeted approaches for prevention and treatment of neuroinflammation in AD.

Discrete placental gene expression signatures accompany diabetic disease classifications during pregnancy

BACKGROUND

Gestational diabetes mellitus affects up to 10% of pregnancies and is classified into subtypes gestational diabetes subtype A1 (GDMA1) (managed by lifestyle modifications) and gestational diabetes subtype A2 (GDMA2) (requiring medication). However, whether these subtypes are distinct clinical entities or more reflective of an extended spectrum of normal pregnancy endocrine physiology remains unclear.

OBJECTIVE

Integrated bulk RNA-sequencing (RNA-seq), single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomics harbors the potential to reveal disease gene signatures in subsets of cells and tissue microenvironments. We aimed to combine these high-resolution technologies with rigorous classification of diabetes subtypes in pregnancy. We hypothesized that differences between preexisting type 2 and gestational diabetes subtypes would be associated with altered gene expression profiles in specific placental cell populations.

STUDY DESIGN

In a large case-cohort design, we compared validated cases of GDMA1, GDMA2, and type 2 diabetes mellitus (T2DM) to healthy controls by bulk RNA-seq (n=54). Quantitative analyses with reverse transcription and quantitative PCR of presumptive genes of significant interest were undertaken in an independent and nonoverlapping validation cohort of similarly well-characterized cases and controls (n=122). Additional integrated analyses of term placental single-cell, single-nuclei, and spatial transcriptomics data enabled us to determine the cellular subpopulations and niches that aligned with the GDMA1, GDMA2, and T2DM gene expression signatures at higher resolution and with greater confidence.

RESULTS

Dimensional reduction of the bulk RNA-seq data revealed that the most common source of placental gene expression variation was the diabetic disease subtype. Relative to controls, we found 2052 unique and significantly differentially expressed genes (-22 thresholds; q<0.05 Wald Test) among GDMA1 placental specimens, 267 among GDMA2, and 1520 among T2DM. Several candidate marker genes (chorionic somatomammotropin hormone 1 [CSH1], period circadian regulator 1 [PER1], phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta [PIK3CB], forkhead box O1 [FOXO1], epidermal growth factor receptor [EGFR], interleukin 2 receptor subunit beta [IL2RB], superoxide dismutase 3 [SOD3], dedicator of cytokinesis 5 [DOCK5], suppressor of glucose, and autophagy associated 1 [SOGA1]) were validated in an independent and nonoverlapping validation cohort (q<0.05 Tukey). Functional enrichment revealed the pathways and genes most impacted for each diabetes subtype, and the degree of proximal similarity to other subclassifications. Surprisingly, GDMA1 and T2DM placental signatures were more alike by virtue of increased expression of chromatin remodeling and epigenetic regulation genes, while albumin was the top marker for GDMA2 with increased expression of placental genes in the wound healing pathway. Assessment of these gene signatures in single-cell, single-nuclei, and spatial transcriptomics data revealed high specificity and variability by placental cell and microarchitecture types. For example, at the cellular and spatial (eg, microarchitectural) levels, distinguishing features were observed in extravillous trophoblasts (GDMA1) and macrophages (GDMA2). Lastly, we utilized these data to train and evaluate 4 machine learning models to estimate our confidence in predicting the control or diabetes status of placental transcriptome specimens with no available clinical metadata.

CONCLUSION

Consistent with the distinct association of perinatal outcome risk, placentae from GDMA1, GDMA2, and T2DM-affected pregnancies harbor unique gene signatures that can be further distinguished by altered placental cellular subtypes and microarchitectural niches.