Metagenomics in Polluted Aquatic Environments

Metagenomics is defined as the culture-independent genomic analysis of biological assemblages providing access to the whole set of genes and genomes from a sample. It encompasses a variety of techniques that are based on (i) total DNA extraction from samples followed by PCR amplification of specific genes, (ii) library construction or amplification and sequencing of the whole genetic material. These methodologies have successfully been applied in studies of composition, dynamics, and functions of microbial communities in a variety of ecosystems including those subjected to anthropogenic modifications (Gilbert & Dupont, 2011). Culture independent methods allow the analysis of a set of metabolic genes from microbial communities, which can be used to determine how environmental conditions such as pollution can shape community composition and the diversity of genes associated with biogeochemical cycles such as those of carbon, nitrogen, and phosphorus (Singh et al., 2009). This approach is also useful for the discovery of novel environmental microorganisms and genes, with important applications for biotechnology, medicine, and bioremediation (Cardoso et al., 2011). This applicability has resulted in a recent sharp increase in studies focusing in the metagenomic analysis of polluted sites. Their aim is to characterize microbial communities from a diverse set of environments such as freshwater, marine sediments, open ocean, pelagic ecosystems, soil, and host-associated communities. An example of these initiatives is the Global Ocean Sampling Expedition (GOS), which assessed the genetic diversity of marine microbial communities around the Earth. Since 2003, an enormous amount of data has been generated by GOS helping scientists to reveal the microbial diversity and also allowing them to better understand microbial phylogeny and ecology (Gilbert & Dupont, 2011)

Spatial and Temporal Dynamics of Prokaryotic and Viral Community Assemblages in a Lotic System (Manatee Springs, Florida)

How from high-magnitude springs fed by the Floridan aquifer system contributes hundreds of liters of water per second to rivers, creating unique lotic systems. Despite their importance as freshwater sources and their contributions to the state's major rivers, little is known about the composition and spatiotemporal variability of prokaryotic and viral communities of these spring systems or their influence on downstream river sites. At four time points throughout a year, we determined the abundance and diversity of prokaryotic and viral communities at three sites within the first-magnitude Manatee Springs system (the spring head where water emerges from the aquifer, a mixed region where the spring run ends, and a downstream site in the Suwannee River). The abundance of prokaryotes and virus-like particles increased 100-fold from the spring head to the river and few members from the head communities persisted in the river at low abundance, suggesting the springs play a minor role in seeding downstream communities. Prokaryotic and viral communities within Manatee Springs clustered by site, with seasonal variability likely driven by flow. As water flowed through the system, microbial community composition was affected by changes in physiochemical parameters and community coalescence. Evidence of species sorting and mass effects could be seen in the assemblages. Greater temporal fluctuations were observed in prokaryotic and viral community composition with increasing distance from the spring outflow, reflecting the relative stability of the groundwater environment, and comparisons to springs from prior work reaffirmed that distinct first-magnitude springs support unique communities.IMPORTANCE Prokaryotic and viral communities are central to food webs and biogeochemical processes in aquatic environments, where they help maintain ecosystem health. The Floridan aquifer system (FAS), which is the primary drinking water source for millions of people in the southeastern United States, contributes large amounts of freshwater to major river systems in Florida through its springs. However, there is a paucity of information regarding the spatiotemporal dynamics of microbial communities in these essential flowing freshwater systems. This work explored the prokaryotic and viral communities in a first-magnitude spring system fed by the FAS that discharges millions of liters of water per day into the Suwannee River. This study examined microbial community composition through space and time as well as the environmental parameters and metacommunity assembly mechanisms that shape these communities, providing a foundational understanding for monitoring future changes

Marine viruses discovered via metagenomics shed light on viral strategies throughout the oceans

Marine viruses are key drivers of host diversity, population dynamics and biogeochemical cycling and contribute to the daily flux of billions of tons of organic matter. Despite recent advancements in metagenomics, much of their biodiversity remains uncharacterized. Here we report a data set of 27,346 marine virome contigs that includes 44 complete genomes. These outnumber all currently known phage genomes in marine habitats and include members of previously uncharacterized lineages. We designed a new method for host prediction based on co-occurrence associations that reveals these viruses infect dominant members of the marine microbiome such as Prochlorococcus and Pelagibacter. A negative association between host abundance and the virus-to-host ratio supports the recently proposed Piggyback-the-Winner model of reduced phage lysis at higher host densities. An analysis of the abundance patterns of viruses throughout the oceans revealed how marine viral communities adapt to various seasonal, temperature and photic regimes according to targeted hosts and the diversity of auxiliary metabolic genes.CAPESCNPqFAPERJCiencia sem fronteiras programUniv Fed Rio de Janeiro, IB, BR-21944970 Rio de Janeiro, BrazilRadboud Univ Nijmegen, Radboud Inst Mol Life Sci, CMBI, Med Ctr, NL-6500 HB Nijmegen, NetherlandsUniv Utrecht, Theoret Biol & Bioinformat, NL-3584 CH Utrecht, NetherlandsSan Diego State Univ, Dept Biol, San Diego, CA 92182 USAUniv Fed Sao Paulo UNIFESP, Dept Ciencias Mar, BR-11070100 Baixada Santista, BrazilNIOZ Royal Netherlands Inst Sea Res, Dept Marine Microbiol & Biogeochem, POB 59, NL-1790 AB Den Burg, NetherlandsUniv Utrecht, POB 59, NL-1790 AB Den Burg, NetherlandsUniv Amsterdam, Dept Aquat Microbiol, IBED, NL-1090 GE Amsterdam, NetherlandsUniv Fed Rio de Janeiro, COPPE, SAGE, BR-21941950 Rio de Janeiro, BrazilUniv Fed Sao Paulo UNIFESP, Dept Ciencias Mar, BR-11070100 Baixada Santista, BrazilCAPESCNPqFAPERJCiencia sem fronteiras program: 864.14.004Web of Scienc

Environmental and sanitary conditions of guanabara bay, Rio de Janeiro

Guanabara Bay is the second largest bay in the coast of Brazil, with an area of 384 km2. In its surroundings live circa 16 million inhabitants, out of which 6 million live in Rio de Janeiro city, one of the largest cities of the country, and the host of the 2016 Olympic Games. Anthropogenic interference in Guanabara Bay area started early in the XVI century, but environmental impacts escalated from 1930, when this region underwent an industrialization process. Herein we present an overview of the current environmental and sanitary conditions of Guanabara Bay, a consequence of all these decades of impacts. We will focus on microbial communities, how they may affect higher trophic levels of the aquatic community and also human health. The anthropogenic impacts in the bay are flagged by heavy eutrophication and by the emergence of pathogenic microorganisms that are either carried by domestic and/or hospital waste (e.g., virus, KPC-producing bacteria, and fecal coliforms), or that proliferate in such conditions (e.g., vibrios). Antibiotic resistance genes are commonly found in metagenomes of Guanabara Bay planktonic microorganisms. Furthermore, eutrophication results in recurrent algal blooms, with signs of a shift toward flagellated, mixotrophic groups, including several potentially harmful species. A recent large-scale fish kill episode, and a long trend decrease in fish stocks also reflects the bay’s degraded water quality. Although pollution of Guanabara Bay is not a recent problem, the hosting of the 2016 Olympic Games propelled the government to launch a series of plans to restore the bay’s water quality. If all plans are fully implemented, the restoration of Guanabara Bay and its shores may be one of the best legacies of the Olympic Games in Rio de Janeiro

Computational methods applied to syphilis: where are we, and where are we going?

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions