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"Luis Rodriguez, M."
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Strengths and Limitations of 16S rRNA Gene Amplicon Sequencing in Revealing Temporal Microbial Community Dynamics
This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GS-FLX-Ti yielding ∼40,000 rRNA gene sequences from each sample and representing ∼300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ∼10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics in situ.
Journal Article
A metabolic gene cluster in Lotus japonicus discloses novel enzyme functions and products in triterpene biosynthesis
Genes for triterpene biosynthetic pathways exist as metabolic gene clusters in oat and Arabidopsis thaliana plants. We characterized the presence of an analogous gene cluster in the model legume Lotus japonicus.
In the genomic regions flanking the oxidosqualene cyclase AMY2 gene, genes for two different classes of cytochrome P450 and a gene predicted to encode a reductase were identified. Functional characterization of the cluster genes was pursued by heterologous expression in Nicotiana benthamiana. The gene expression pattern was studied under different developmental and environmental conditions. The physiological role of the gene cluster in nodulation and plant development was studied in knockdown experiments.
A novel triterpene structure, dihydrolupeol, was produced by AMY2. A new plant cytochrome P450, CYP71D353, which catalyses the formation of 20-hydroxybetulinic acid in a sequential three-step oxidation of 20-hydroxylupeol was characterized. The genes within the cluster are highly co-expressed during root and nodule development, in hormone-treated plants and under various environmental stresses. A transcriptional gene silencing mechanism that appears to be involved in the regulation of the cluster genes was also revealed.
A tightly co-regulated cluster of functionally related genes is involved in legume triterpene biosynthesis, with a possible role in plant development.
Journal Article
Pharmacological disruption of mSWI/SNF complex activity restricts SARS-CoV-2 infection
Identification of host determinants of coronavirus infection informs mechanisms of viral pathogenesis and can provide new drug targets. Here we demonstrate that mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) chromatin remodeling complexes, specifically canonical BRG1/BRM-associated factor (cBAF) complexes, promote severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and represent host-directed therapeutic targets. The catalytic activity of SMARCA4 is required for mSWI/SNF-driven chromatin accessibility at the
ACE2
locus,
ACE2
expression and virus susceptibility. The transcription factors HNF1A/B interact with and recruit mSWI/SNF complexes to
ACE2
enhancers, which contain high HNF1A motif density. Notably, small-molecule mSWI/SNF ATPase inhibitors or degraders abrogate angiotensin-converting enzyme 2 (ACE2) expression and confer resistance to SARS-CoV-2 variants and a remdesivir-resistant virus in three cell lines and three primary human cell types, including airway epithelial cells, by up to 5 logs. These data highlight the role of mSWI/SNF complex activities in conferring SARS-CoV-2 susceptibility and identify a potential class of broad-acting antivirals to combat emerging coronaviruses and drug-resistant variants.
The canonical BRG1/BRM-associated factor (cBAF) complex is recruited by HNF1A/B to angiotensin-converting enzyme 2 (ACE2) enhancers, promoting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Inhibition of the catalytic activity of SMARCA4 precludes
ACE2
expression and reduces susceptibility to SARS-CoV-1 and major SARS-CoV-2 variants.
Journal Article
SAR11 bacteria linked to ocean anoxia and nitrogen loss
Bacteria of the SAR11 clade constitute up to one half of all microbial cells in the oxygen-rich surface ocean. SAR11 bacteria are also abundant in oxygen minimum zones (OMZs), where oxygen falls below detection and anaerobic microbes have vital roles in converting bioavailable nitrogen to N
2
gas. Anaerobic metabolism has not yet been observed in SAR11, and it remains unknown how these bacteria contribute to OMZ biogeochemical cycling. Here, genomic analysis of single cells from the world’s largest OMZ revealed previously uncharacterized SAR11 lineages with adaptations for life without oxygen, including genes for respiratory nitrate reductases (Nar). SAR11
nar
genes were experimentally verified to encode proteins catalysing the nitrite-producing first step of denitrification and constituted ~40% of OMZ
nar
transcripts, with transcription peaking in the anoxic zone of maximum nitrate reduction activity. These results link SAR11 to pathways of ocean nitrogen loss, redefining the ecological niche of Earth’s most abundant organismal group.
Bacteria of the SAR11 clade constitute up to one half of all marine microbes and are thought to require oxygen for growth; here, a subgroup of SAR11 bacteria are shown to thrive in ocean oxygen minimum zones and to encode abundant respiratory nitrate reductases.
An anoxic niche for SAR11 bacteria
SAR11 bacteria, the most abundant type of microbe in the world's oceans, are thought to require oxygen for growth, yet they are also abundant in waters where oxygen levels are low. Frank Stewart and colleagues show here that a subgroup of SAR11 bacteria that thrives in ocean oxygen minimum zones have adapted to the microaerobic/anaerobic conditions there, and they encode abundant respiratory nitrate reductases that perform the first step in denitrification. These results redefine the ecological niche of Earth's most abundant organismal group and suggest that they are substantial contributors to nitrogen loss in oxygen minimum zones.
Journal Article
Zinc-sensitive MRI contrast agent detects differential release of Zn(II) ions from the healthy vs. malignant mouse prostate
Many secretory tissues release Zn(II) ions along with other molecules in response to external stimuli. Here we demonstrate that secretion of Zn(II) ions from normal, healthy prostate tissue is stimulated by glucose in fasted mice and that release of Zn(II) can be monitored by MRI. An ∼50% increase in water proton signal enhancement is observed in T₁-weighted images of the healthy mouse prostate after infusion of a Gd-based Zn(II) sensor and an i.p. bolus of glucose. Release of Zn(II) from intracellular stores was validated in human epithelial prostate cells in vitro and in surgically exposed prostate tissue in vivo using a Zn(II)-sensitive fluorescent probe known to bind to the extracellular surface of cells. Given the known differences in intracellular Zn(II) stores in healthy versus malignant prostate tissues, the Zn(II) sensor was then evaluated in a transgenic adenocarcinoma of the mouse prostate (TRAMP) model in vivo. The agent proved successful in detecting small malignant lesions as early as 11 wk of age, making this noninvasive MR imaging method potentially useful for identifying prostate cancer in situations where it may be difficult to detect using current multiparametric MRI protocols.
Journal Article
High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries
A fundamental question in microbiology is whether there is continuum of genetic diversity among genomes, or clear species boundaries prevail instead. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) help address this question by facilitating high resolution taxonomic analysis of thousands of genomes from diverse phylogenetic lineages. To scale to available genomes and beyond, we present FastANI, a new method to estimate ANI using alignment-free approximate sequence mapping. FastANI is accurate for both finished and draft genomes, and is up to three orders of magnitude faster compared to alignment-based approaches. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal clear genetic discontinuity, with 99.8% of the total 8 billion genome pairs analyzed conforming to >95% intra-species and <83% inter-species ANI values. This discontinuity is manifested with or without the most frequently sequenced species, and is robust to historic additions in the genome databases.
Average Nucleotide Identity (ANI) is a robust and useful measure to gauge genetic relatedness between two genomes. Here, the authors develop FastANI, a method to compute ANI using alignment-free approximate sequence mapping, and show 95% ANI is an accurate threshold for demarcating prokaryotic species by analyzing about 90,000 prokaryotic genomes.
Journal Article
Toward state-of-the-art on social marketing research in user-generated content (UGC) and influencers
PurposeThis study examines the research that has been conducted on user-generated advertising content in the social marketing strategies of commercial brands to understand the phenomenon, explore academic interest in the topic and identify areas of limited thematic coverage.Design/methodology/approachA systematic review of existing scientific literature in the Web of Science (WoS) and Scopus was carried out using the PRISMA protocol. A co-occurrence matrix was used to review emerging topics on user-generated content (UGC) and influencer marketing, allowing the identification of articles (n = 59) related to the objective of this research.FindingsMost research has analyzed UGC in images or text, but only very few have addressed videos and other digital formats (such as reels, image carousels or podcasts), although there is sufficient work focused on Twitter, Facebook and YouTube. There was no evidence of work exploring the effects, repercussions and possible dangers of uncontrolled brand exposure through Unofficial Brand Ambassadors.Originality/valueThe literature review has allowed finding important areas of future research that the scientific community has not sufficiently addressed. Likewise, this work shows structurally several classifications of UGC, which will facilitate future research to deepen and broaden these categories.
Journal Article
From nuclear track characterization to machine learning based image classification in neutron autoradiography for boron neutron capture therapy
Knowledge of the 10 B microdistribution is of great relevance in BNCT studies. Since 10 B concentration assesment through neutron autoradiography depends on the correct quantification of tracks in a nuclear track detector, image acquisition and processing conditions should be controlled and verified, in order to obtain accurate results to be applied in the frame of BNCT. With this aim, an image verification process was proposed, based on parameters extracted from the quantified nuclear tracks. Track characterization was performed by selecting a set of morphological and pixel-intensity uniformity parameters from the quantified objects (area, diameter, roundness, aspect ratio, heterogeneity and clumpiness). Their distributions were studied, leading to the observation of varying behaviours in images generated by different samples and acquisition conditions. The distributions corresponding to samples coming from the BNC reaction showed similar attributes in each analyzed parameter, proving to be robust to the experimental process, but sensitive to light and focus conditions. Considering those observations, a manual feature extraction was performed as a pre-processing step. A Support Vector Machine (SVM) and a fully dense Neural Network (NN) were optimized, trained, and tested. The final performance metrics were similar for both models: 93%-93% for the SVM, vs 94%-95% for the NN in accuracy and precision respectively. Based on the distribution of the predicted class probabilities, the latter had a better capacity to reject inadequate images, so the NN was selected to perform the image verification step prior to quantification. The trained NN was able to correctly classify the images regardless of their track density. The exhaustive characterization of the nuclear tracks provided new knowledge related to the autoradiographic images generation. The inclusion of machine learning in the analysis workflow proves to optimize the boron determination process and paves the way for further applications in the field of boron imaging.
Journal Article
An ANI gap within bacterial species that advances the definitions of intra-species units
Large-scale surveys of prokaryotic communities (metagenomes), as well as isolate genomes, have revealed that their diversity is predominantly organized in sequence-discrete units that may be equated to species. Specifically, genomes of the same species commonly show genome-aggregate average nucleotide identity (ANI) >95% among themselves and ANI <90% to members of other species, while genomes showing ANI 90%–95% are comparatively rare. However, it remains unclear if such “discontinuities” or gaps in ANI values can be observed within species and thus used to advance and standardize intra-species units. By analyzing 18,123 complete isolate genomes from 330 bacterial species with at least 10 genome representatives each and available long-read metagenomes, we show that another discontinuity exists between 99.2% and 99.8% (midpoint 99.5%) ANI in most of these species. The 99.5% ANI threshold is largely consistent with how sequence types have been defined in previous epidemiological studies but provides clusters with ~20% higher accuracy in terms of evolutionary and gene-content relatedness of the grouped genomes, while strains should be consequently defined at higher ANI values (>99.99% proposed). Collectively, our results should facilitate future micro-diversity studies across clinical or environmental settings because they provide a more natural definition of intra-species units of diversity. Bacterial strains and clonal complexes are two cornerstone concepts for microbiology that remain loosely defined, which confuses communication and research. Here we identify a natural gap in genome sequence comparisons among isolate genomes of all well-sequenced species that has gone unnoticed so far and could be used to more accurately and precisely define these and related concepts compared to current methods. These findings advance the molecular toolbox for accurately delineating and following the important units of diversity within prokaryotic species and thus should greatly facilitate future epidemiological and micro-diversity studies across clinical and environmental settings.
Journal Article