Ice and water microbial communities from Lake Winnipeg were explored through V4 region 16S rRNA gene sequencing during a pronounced period of cold temperatures over North America's Great Plains and Great Lakes regions. Diatoms, cyanobacteria, and Xanthomonadales (Gammaproteobacteria) displayed patterns of partitioning into ice fractions.

ABSTRACT The Winam Gulf in the Kenyan region of Lake Victoria experiences prolific, year-round cyanobacterial harmful algal blooms (cyanoHABs) which pose threats to human, livestock, and ecosystem health. To our knowledge, there is limited molecular research on the gulf’s cyanoHABs, and thus, the strategies employed for survival and proliferation by toxigenic cyanobacteria in this region remain largely unexplored. Here, we used metagenomics to analyze the Winam Gulf’s cyanobacterial composition, function, and biosynthetic potential. Dolichospermum was the dominant bloom-forming cyanobacterium, co-occurring with Microcystis at most sites. Microcystis and Planktothrix were more abundant in shallow and turbid sites. Metagenome-assembled genomes (MAGs) of Dolichospermum harbored nitrogen fixation genes, suggesting diazotrophy as a potential mechanism supporting the proliferation of Dolichospermum in the nitrogen-limited gulf. Over 300 biosynthetic gene clusters (BGCs) putatively encoding the synthesis of toxins and other secondary metabolites were identified across the gulf, even at sites where there were no visible cyanoHAB events. Almost all BGCs identified had no known synthesis product, indicating a diverse and novel biosynthetic repertoire capable of synthesizing harmful or potentially therapeutic metabolites. Microcystis MAGs contained mcy genes encoding the synthesis of hepatotoxic microcystins which are a concern for drinking water safety. These findings illustrate the spatial variation of bloom-forming cyanobacteria in the Winam Gulf and their available strategies to dominate different ecological niches. This study underscores the need for further use of genomic techniques to elucidate the dynamics and mitigate the potentially harmful effects of cyanoHABs and their associated toxins on human, environmental, and economic health. IMPORTANCE The Winam Gulf (Kenya) is a vital resource that experiences prolific cyanobacterial harmful algal blooms (cyanoHABs). Bloom-forming cyanobacteria produce cyanotoxins, threatening human and environmental health, recreation, and fishing. However, cyanotoxin production in the gulf has not been linked to a specific type of cyanobacteria. We used DNA sequencing of whole microbial communities to track the species of cyanobacteria present across the gulf and investigate the genes responsible for synthesis of known and novel toxins. Our results reveal Dolichospermum as the main bloom-forming cyanobacteria in the gulf, often co-occurring with high abundance of toxigenic Microcystis. Over 300 unique gene clusters were found, with most predicted to encode the synthesis of uncharacterized molecules. These results provide initial insights into the diverse biosynthetic potential encoded by cyanobacteria in the Winam Gulf and underscore the need to further elucidate and investigate the effects of known and novel molecules produced in cyanoHABs in this region.

Conventional metrics for tracking infectious diseases, including case and outbreak data and syndromic surveillance, can be resource-intensive, misleading, and comparatively slow with prolonged data collection, analysis and authentication. This study examined the 2022-2023 Respiratory Syncytial Virus (RSV) season in a contiguous metropolitan area connected by an active international land border, affording an opportunity for comparison of the respiratory virus season spanning two independent public health jurisdictions. Time-lagged cross correlation and qualitative examination of the wastewater signals showed that the peak of the Detroit (MI, USA) RSV season predated the peak in Windsor (ON, Canada) by approximately 5 weeks. A strong positive relationship was observed between RSV N-gene concentrations in wastewater and hospitalization rates in Windsor-Essex (Kendall's τ = 0.539, p ≤ 0.001, Spearman's ρ = 0.713, p ≤ 0.001) as well as Detroit (Kendall's τ = 0.739, p ≤ 0.001, Spearman's ρ = 0.888, p ≤ 0.001). This study demonstrated that wastewater surveillance can reveal regional differences in infection dynamics between communities and can provide an independent measure of the prevalence of RSV, an underreported disease. These findings support the use of wastewater surveillance as a cost-effective tool in monitoring of RSV to enhance existing surveillance systems and to better inform public health disease mitigation strategies.

Real-time monitoring of phytoplankton in freshwater systems is critical for early detection of harmful algal blooms (HABs) to enable efficient response by water management agencies. This manuscript presents an image processing pipeline developed to adapt ARTiMiS, a low-cost automated flow-imaging device, for real-time algal monitoring in natural freshwater systems. This pipeline addresses several challenges associated with autonomous imaging of aquatic samples, such as flow-imaging artifacts (i.e., out-of-focus and background objects), as well as strategies to efficiently identify novel objects that are not represented in the training data set; the latter is a common challenge with the application of deep learning approaches for image classification in environmental systems. The pipeline leverages a random forest model to identify out-of-focus particles with an accuracy of 89% and a custom background particle detection algorithm to identify and remove particles that erroneously appear in consecutive images with >97 ± 2.8% accuracy. Furthermore, a convolutional neural network (CNN), trained to classify taxonomical classes, achieved 95% accuracy in a closed set classification. Nonetheless, the supervised closed-set classifiers struggled with the accurate classification of objects when challenged with novel particles, which are common in complex natural environments; this limits real-time monitoring applications by requiring extensive manual oversight. To mitigate this, three methods incorporating classification with rejection were tested to improve model precision by flagging irrelevant or unknown classes. Combined, these advances present a fully integrated, end-to-end solution for real-time HAB monitoring in natural freshwater systems, which enhances the scalability of automated detection in dynamic aquatic environments.

Despite the global expansion of cyanobacterial harmful algal blooms (cHABs), research is biased to temperate systems within the global north, such as the Laurentian Great Lakes. This lack of diversity represents a significant gap in the field and jeopardizes the health of those who reside along at-risk watersheds in the global south. The African Great Lake, Lake Victoria, is understudied despite serving as the second largest lake by surface area and demonstrating year-round cHABs. Here, we address this knowledge gap by performing a molecular survey of cHAB communities in three anthropogenically and ecologically important freshwater systems of Victoria's Kenyan watershed: Winam Gulf (Lake Victoria), Lake Simbi and Lake Naivasha. We identified a bloom of non-toxic Dolichospermum and toxic Microcystis in the Winam Gulf, with data suggesting sulfur limitation shapes competition dynamics between these two bloom-formers. Though we did not detect a bloom in Naivasha, it contained the largest diversity of cHAB genera amongst the three lakes. In turn, our results indicated methane metabolism may allow non-toxic picoplankton to outcompete cHAB genera, while suggesting Synechococcus spp. serves as a methane source and sink in this system. Lake Simbi exhibited a non-toxic Limnospira bloom at the time of sampling with very low abundances of cHAB genera present. Subsequently, these results were employed to design a cHAB screening and risk assessment framework for local stakeholders. Cumulatively, this work serves to increase cHAB research efforts on the international scale while serving as an impetus for cHAB monitoring on the local scale.

We report 40 metagenomic libraries collected from the Winam Gulf of Lake Victoria during May-July of 2022-2023 and an additional eight opportunistic libraries from adjacent Lakes Simbi, Naivasha, and regional river systems. The sampling period captured cyanobacterial bloom events - shedding insight onto community composition and genomic potential.

Freshwater lakes are sentinels of environmental change, and climate change-driven declines in ice cover have been shown to disrupt aquatic communities and jeopardize ecosystem services. Viruses shape microbial communities and regulate biogeochemical cycles by acting as top-down controls, yet there is relatively little known about how declining ice cover will influence viral community activity. Lake Erie is a critical freshwater ecosystem and serves as a model system to assess how ice cover extent will affect winter limnology. We surveyed size selected surface water metatranscriptomes for conserved viral hallmark genes as a proxy for active virus populations and compared activity profiles between ice-covered and ice-free conditions from two contrasting winters. Active virus communities were present in both conditions, spanning diverse phylogenetic clades of bacteriophage ( Caudovirales ), giant viruses ( Nucleocytoviricota ), and RNA viruses ( Orthornavirae ). However, viral activity was significantly shaped by the extent of ice cover. Notably, viral richness and relative transcript abundance in the surface waters were reduced under ice relative to the ice-free conditions. Correlations with microbial community metrics suggest the differences in viral communities are at least in part driven by the decreased winter diatom bloom associated with declines in ice cover. Overall, our data suggest viral community activity is influenced by ice cover extent, and viruses may serve as sentinels of environmental disturbance and ecosystem response(s) to climate change. IMPORTANCE As ice cover is projected to become increasingly rare on large temperate lakes, there is a need to understand how microbial communities during winter months might respond to these changing ice-cover conditions. Despite the documented controls viruses have on microbial communities, little is known regarding the relationship between virus activity and ice cover extent. By using metatranscriptomics to investigate virus communities, we show that viral community activity is sensitive to ice cover extent, likely due in part to ice cover-driven shifts in host community structure. This work serves to build our understanding of how viral communities will function in a future, potentially ice-free, climate. ### Competing Interest Statement The authors have declared no competing interest.

During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province's and 26.2% of Canada's population. Sampling occurred 2-7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance's role in estimating disease incidence in Ontario.

Phytoplankton community composition in tributaries differs from that in their receiving waters, due to light limitation from suspended particles and other factors such as nutrient availability and temperature. This study was designed to manipulate light levels in early, mid, and late summer to determine the combined effects of light attenuation and naturally varying nutrient availability on phytoplankton community composition in an agriculturally-influenced tributary of the lower Great Lakes. In all trials, in situ microcosm experiments show that phytoplankton abundance increased under three light attenuation treatments (60 %, 75 %, and 85 % attenuation) relative to time-zero, but higher light attenuation reduced total phytoplankton abundance relative to controls. Highest phytoplankton diversity in terms of richness and evenness occurred in September (late summer), and across all three trials was lowest under the highest light attenuation treatments (85 %). Phytoplankton community composition followed a normal seasonal shift from diatoms dominating in June (early summer), followed by cyanobacteria dominating in mid to late summer. In general, lower light levels (especially 85 % attenuation) corresponded with an increased dominance of cyanobacteria. These findings support the hypothesis that phytoplankton abundance and diversity vary with light and nutrient availability and that light attenuation promotes the shift from buoyant cyanobacteria to other taxa more tolerant of low light levels.

COVID-19 has been a global public health and economic challenge. Screening for the SARS-CoV-2 virus has been a key part of disease mitigation while the world continues to move forward, and lessons learned will benefit disease detection beyond COVID-19. Saliva specimen collection offers a less invasive, time- and cost-effective alternative to standard nasopharyngeal swabs. We optimized two different methods of saliva sample processing for RT-qPCR testing. Two methods were optimized to provide two cost-efficient ways to do testing for a minimum of four samples by pooling in a 2.0 mL tube and decrease the need for more highly trained personnel. Acid-pH-based RNA extraction method can be done without the need for expensive kits. Direct Lysis is a quick one-step reaction that can be applied quickly. Our optimized Acid-pH and Direct Lysis protocols are reliable and reproducible, detecting the beta-2 microglobulin (B2M) mRNA in saliva as an internal control from 97 to 96.7% of samples, respectively. The cycle threshold (Ct) values for B2M were significantly higher in the Direct Lysis protocol than in the Acid-pH protocol. The limit of detection for N1 gene was higher in Direct Lysis at ≤ 5 copies/μL than Acid-pH. Saliva samples collected over the course of several days from two COVID-positive individuals demonstrated Ct values for N1 that were consistently higher from Direct Lysis compared to Acid-pH. Collectively, this work supports that each of these techniques can be used to screen for SARS-CoV-2 in saliva for a cost-effective screening platform.

Climate change, overfishing, pollution, and habitat degradation are no longer distant threats and demand our collective action. Rising to this challenge, the Aquatic Resources and Blue Economy Conference (ARBEC) held in Kisumu, Kenya served as a call to action for sustainable aquatic practices and protection of blue economy resources. The blue economy holds much promise yet as the global community faces unprecedented environmental challenges, it’s potential hinges on our ability to make informed, science-driven decisions.

Background Day-to-day variation in the measurement of SARS-CoV-2 in wastewater can challenge public health interpretation. We assessed a Bayesian smoothing and forecasting method previously used for surveillance and short-term projection of COVID-19 cases, hospitalizations, and deaths. Methods SARS-CoV-2 viral measurement from the sewershed in Ottawa, Canada, sampled at the municipal wastewater treatment plant from July 1, 2020, to February 15, 2022, was used to assess and internally validate measurement averaging and prediction. External validation was performed using viral measurement data from influent wastewater samples from 15 wastewater treatment plants and municipalities across Ontario. Results Plots of SARS-CoV-2 viral measurement over time using Bayesian smoothing visually represented distinct COVID-19 “waves” described by case and hospitalization data in both initial (Ottawa) and external validation in 15 Ontario communities. The time-varying growth rate of viral measurement in wastewater samples approximated the growth rate observed for cases and hospitalization. One-week predicted viral measurement approximated the observed viral measurement throughout the assessment period from December 23, 2020, to August 8, 2022. An uncalibrated model showed underprediction during rapid increases in viral measurement (positive growth) and overprediction during rapid decreases. After recalibration, the model showed a close approximation between observed and predicted estimates. Conclusion Bayesian smoothing of wastewater surveillance data of SARS-CoV-2 allows for accurate estimates of COVID-19 growth rates and one- and two-week forecasting of SARS-CoV-2 in wastewater for 16 municipalities in Ontario, Canada. Further assessment is warranted in other communities representing different sewersheds and environmental conditions.

The Great Lakes and connecting waters encompass a vast and diverse ecosystem that presents scale challenges for management similar to those of the coastal ocean. Technological approaches to overcome the scale challenges have primarily been adapted from oceanographic applications and technologies, and from upscaling inland lake methods designed for shallower and calmer water bodies. Many standard methods for studying Great Lakes habitat and biota have long lag times between field collection and data availability. Many also miss much of the dynamics, three-dimensional complexity, and spatial variability needed to manage the system effectively. Even baseline conditions are not well characterized for many parts of the Great Lakes ecosystem (e.g. bathymetry and critical habitat, life cycles and food webs, night and winter movement and activity of organisms). Emerging technologies are beginning to address these needs but require coordination, consistent investment, training, and governance linkages. Here we survey recent technological advances and show how they are contributing to improved adaptive management of the Great Lakes ecosystem by reducing uncertainty and increasing understanding of physical, biological, and chemical processes, and the human dimensions of resource management and restoration.

The Nile perch (Lates niloticus L.) commercial fishery for Lake Victoria in East Africa is an important source of revenue and employment. We focused on shifts in food web structure and total mercury (THg) bioaccumulation and biomagnification in Nile perch, and lower food web items collected from Winam Gulf (Kenya) sampled 24 years apart (1998 and 2022). Stable isotope carbon (delta 13C) values were higher in all species from 2022 compared to 1998. Stable nitrogen isotope (delta 15N) values in baseline organisms were lower in 2022 compared to 1998. In Nile perch, delta 15N values were correlated with total length, but the delta 15N-length regressions were steeper in 1998 compared to 2022 except for one large (158 cm) Nile perch from 1998 with an uncharacteristically low delta 15N value. Total Hg concentrations were lower in lower trophic species from 2022 compared to 1998. However, the THg bioaccumulation rate (as a function of fish length) in Nile perch was greater in 2022 compared to 1998 resulting in 24.2 % to 42.4 % higher wet weight dorsal THg concentrations in 2022 Nile perch for market slot size (50 to 85 cm) fish. The contrasting observations of increased THg bioaccumulation with size in 2022 against decreases in the rate of trophic increase with size and lower THg concentrations of lower food web items imply reduced fish growth and potential bioenergetic stressors on Winam Gulf Nile perch. All samples except 1 large Nile perch (139 cm total length collected in 2022) had THg concentrations below the European Union trade limit (500 ng/g wet weight). However, for more vulnerable individuals (women, children and frequent fish eaters), we recommend a decrease in maximum monthly meal consumption for 55-75 cm Nile perch from 16 meals per month calculated for 1998 to a limit of 8 meals per month calculated for 2022.

Wastewater surveillance is an effective way to track the prevalence of infectious agents within a community and, potentially, the spread of pathogens between jurisdictions. We conducted a retrospective wastewater surveillance study of the 2022–23 influenza season in 2 communities, Detroit, Michigan, USA, and Windsor-Essex, Ontario, Canada, that form North America’s largest cross-border conurbation. We observed a positive relationship between influenza-related hospitalizations and the influenza A virus (IAV) wastewater signal in Windsor-Essex (ρ = 0.785; p<0.001) and an association between influenza-related hospitalizations in Michigan and the IAV wastewater signal for Detroit (ρ = 0.769; p<0.001). Time-lagged cross correlation and qualitative examination of wastewater signal in the monitored sewersheds showed the peak of the IAV season in Detroit was delayed behind Windsor-Essex by 3 weeks. Wastewater surveillance for IAV reflects regional differences in infection dynamics which may be influenced by many factors, including the timing of vaccine administration between jurisdictions.

Components of the lower food web (mussels, Caridina and Omena) were collected from stations from Winam Gulf, Lake Victoria, Kenya in 2022 and 2023 to analyze for stable isotopes and total mercury (THg). Temporal comparisons were made with data generated for the same species in 1998. Values of δ15N in mussels and Caridina were similar (6.89‰ vs. 6.78 ± 0.13‰), while Omena occupied an elevated trophic position (9.97 ± 0.24‰) with minor shifts in δ15N over time. All species had elevated δ13C values in 2022–2023 versus 1998 supportive of enhanced eutrophication in the Gulf. THg concentrations exhibited modest spatial differences between sites (< 2.6 fold), but not between Caridina and Omena. Larger temporal differences were apparent relative to spatial patterns with THg concentrations decreasing in study species by 2.8 to 4.1-fold between years. An exposure assessment indicated that Omena, commonly found in local markets, can be consumed up to 0.74 kg/month without generating excess THg exposures.

Organism abundance and diversity were assessed in Lake Erie ice samples using sequences derived from a combined metagenomic and metatranscriptomic analysis. The 68,417 unique sequences were from Bacteria (77.5%), Eukarya (22.3%), and Archaea (0.2%) and indicated diverse species of organisms from 32 bacterial, 8 eukaryotic, and 2 archaeal taxonomic groups.

[This corrects the article DOI: 10.3389/fmicb.2022.1075621.].

Lake Erie algal bloom discussions have historically focused on cyanobacteria, with foundational “blooms like it hot” and “high nutrient” paradigms considered as primary drivers behind cyanobacterial bloom success. Yet, recent surveys have rediscovered winter-spring diatom blooms, introducing another key player in the Lake Erie eutrophication and algal bloom story which has been historically overlooked. These blooms (summer vs. winter) have been treated as solitary events separated by spatial and temporal gradients. However, new evidence suggests they may not be so isolated, linked in a manner that manifests as an algal bloom cycle. Equally notable are the emerging reports of cyanobacterial blooms in cold and/or oligotrophic freshwaters, which have been interpreted by some as shifts in classical bloom paradigms. These emerging bloom reports have led many to ask “what is a bloom?”. Furthermore, questioning classic paradigms has caused others to wonder if we are overlooking additional factors which constrain bloom success. In light of emerging data and ideas, we revisited foundational concepts within the context of Lake Erie algal blooms and derived five key take-aways: 1) Additional bloom-formers (diatoms) need to be included in Lake Erie algal discussions, 2) The term “bloom” must be reinforced with a clear definition and quantitative metrics for each event, 3) Algal blooms should not be studied solitarily, 4) Shifts in physiochemical conditions serve as an alternative interpretation to potential shifts in ecological paradigms, 5) Additional factors which constrain bloom success and succession (i.e., pH and light) require consideration.