Biology subjects

Kim, G.-Y.

Publications and source records attributed to Kim, G.-Y..

3 recordsLinked to original sources

bioRxiv2026

Systematic comparisons between long-read and short-read based amplicon sequencing to characterize mixed microalgal communities.

The 18S rRNA gene has emerged as the primary molecular marker for amplicon-based characterization of microalgal communities, including in wastewater treatment systems, yet trade-offs between short- and long-read approaches remain poorly defined. We systematically compared V8-V9 short-read sequencing (Illumina MiSeq), full-length long-read sequencing with ss5ss3 primers (PacBio Sequel II), and computationally extracted V8-V9 regions from long-read data. Both in silico and in vitro analyses confirmed V8-V9 captured broader taxonomic coverage than ss5ss3, though partial reference sequences and taxonomic mis-annotations biased in silico assessments. Long-reads taxonomic advantage was database-dependent, constrained by SILVA databases genus-level curation but fully realized when paired with the species-level-curated and eukaryotes-focused PR{superscript 2} (Protist Ribosomal Reference) database. Long-read sequencing uniquely identified amplicon sequence variants (ASVs) assigned to key phosphorus assimilators (Scenedesmus obliquus, Desmodesmus sp., and Acutodesmus sp.) at species level during successful phosphorus removal in a full-scale microalgal cultivation system, while V8-V9 short-read sequencing revealed ASVs assigned to algal-predatory (Leptophryidae) and bacterivorous (Choanoflagellata and Rhogostoma-lineage) protists when performance declined, suggesting grazing pressure on the phosphorus-removing community. Although both approaches performed comparably for operational monitoring, these complementary strengths support short-read sequencing for routine community profiling and long-read sequencing for detailed functional investigations of Chlorophyta.

microbiology↗

bioRxiv2024

Morphotype-Resolved Characterization of Microalgal Communities in a Nutrient Recovery Process with ARTiMiS Flow Imaging Microscopy

Microalgae-driven nutrient recovery represents a promising technology to reduce effluent phosphorus while simultaneously generating biomass that can be valorized to offset treatment costs. As full-scale processes come online, system parameters including biomass composition must be carefully monitored to optimize performance and prevent culture crashes. In this study, flow imaging microscopy (FIM) was leveraged to characterize microalgal community composition in near real-time at a full-scale municipal wastewater treatment plant (WWTP) in Wisconsin, USA, and population and morphotype dynamics were examined to identify relationships between water chemistry, biomass composition, and system performance. Two FIM technologies, FlowCam and ARTiMiS, were evaluated as monitoring tools. ARTiMiS provided a more accurate estimate of total system biomass, and estimates derived from particle area as a proxy for biovolume yielded better approximations than particle counts. Deep learning classification models trained on annotated image libraries demonstrated equivalent performance between FlowCam and ARTiMiS, and convolutional neural network (CNN) classifiers proved significantly more accurate when compared to feature table-based deep neural network (DNN) models. Across a two-year study period, Scenedesmus spp. appeared most important for phosphorus removal, which were negatively associated with elevated temperatures and nitrite/nitrate concentrations. Chlorella and Monoraphidium also played an important role in system performance. For both Scenedesmus and Chlorella, smaller morphological types were more often associated with high system performance, whereas larger morphotypes implied a stress response correlating with poor phosphorus recovery rates. These results demonstrate the potential of FIM as a critical technology for high-resolution characterization of industrial microalgal processes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/628756v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1023934org.highwire.dtl.DTLVardef@f9b4a0org.highwire.dtl.DTLVardef@1c193a6org.highwire.dtl.DTLVardef@1c48ec1_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Community Structure and Function During Periods of High Performance and System Upset in a Full-Scale Mixed Microalgal Wastewater Resource Recovery Facility

Microalgae have the potential to exceed current nutrient recovery limits from wastewater, enabling water resource recovery facilities (WRRFs) to achieve increasingly stringent effluent permits. The use of photobioreactors (PBRs) and the separation of hydraulic retention and solids residence time (HRT/SRT) further enables increased biomass in a reduced physical footprint while allowing operational parameters (e.g., SRT) to select for desired functional communities. However, as algal technology transitions to full-scale, there is a need to understand the effect of operational and environmental parameters on complex microbial dynamics among mixotrophic microalgae, bacterial groups, and pests (i.e., grazers and pathogens) and to implement robust process controls for stable long-term performance. Here, we examine the first full-scale, intensive WRRF utilizing mixed microalgal for tertiary treatment in the US (EcoRecover, Clearas Water Recovery Inc.) during a nine-month monitoring campaign. We investigated the temporal variations in microbial community structure (18S and 16S rRNA genes), which revealed that stable system performance of the EcoRecover system was marked by a low-diversity microalgal community (DINVSIMPSON = 2.01) dominated by Scenedesmus sp. (MRA = 55%-80%) that achieved strict nutrient removal (effluent TP < 0.04 mg{middle dot}L-1) and steady biomass production (TSSmonthly avg. = 400-700 mg{middle dot}L-1). Operational variables including pH, alkalinity, and influent ammonium (NH4+), correlated positively (p < 0.05, method = Spearman) with algal community during stable performance. Further, the use of these parameters as operational controls along with N/P loading and SRT allowed for system recovery following upset events. Importantly, the presence or absence of bacterial nitrification did not directly impact algal system performance and overall nutrient recovery, but partial nitrification (potentially resulting from NO2- accumulation) inhibited algal growth and should be considered during long-term operation. The microalgal communities were also adversely affected by zooplankton grazers (ciliates, rotifers) and fungal parasites (Aphelidium), particularly during periods of upset when algal cultures were experiencing culture turnover or stress conditions (e.g., nitrogen limitation, elevated temperature). Overall, the active management of system operation in order to maintain healthy algal cultures and high biomass productivity can result in significant periods (>4 months) of stable system performance that achieve robust nutrient recovery, even in winter months in northern latitudes (WI, USA). Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/576871v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@15ef2a4org.highwire.dtl.DTLVardef@8c1de6org.highwire.dtl.DTLVardef@ff1160org.highwire.dtl.DTLVardef@1cded87_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMicrobial dynamics were examined for first full-scale, intensive (small footprint) algal wastewater treatment process (EcoRecover) for advanced P removal. C_LIO_LIMixed microbial communities during stable performance were dominated by Scenedesmus and Cyanobacteria and positively correlated with pH, alkalinity, and influent NH4+, among other parameters. C_LIO_LIBacterial nitrification did not benefit or hinder nutrient recovery, but partial nitrification and NO2- accumulation inhibited algal growth. C_LIO_LITaxa specific pest dynamics are described, with major outbreaks occurring during high temperature in summer months. C_LIO_LIControl of operational parameters, and recovery of stable system performance and algal biomass was achieved following system upsets. C_LI

bioengineering↗