Mass spectrometry-based proteomic analysis of plasma is a vital tool for biomarker discovery, yet it is hindered by high-abundance proteins, which can obscure the detection of low-abundance biomarkers. Nanotrap® Protein Enrichment Affinity Kit (PEAK) is a simple, versatile, and easy-to-use kit that improves the detection of low-abundance proteins from multiple sample types. These kits utilize the Nanotrap® magnetic hydrogel particle technology to enrich low-abundance proteins from complex sample matrices. In this study, three different Nanotrap® Protein Particle types and multiple particle combinations for plasma processing were evaluated. Each workflow offers unique benefits, allowing researchers to tailor their approach. Additionally, we investigated whether a simple 30-minute enrichment step using Nanotrap® PEAK would enhance protein identification in plasma, cerebrospinal fluid (CSF), and urine samples. SKU # 34XXX Literature # PL-PO31442

INTRODUCTION Plasma proteomics is inherently challenging due to its extreme dynamic range, with a small number of highly abundant proteins dominating the sample and limiting detection of lower-abundance, biologically relevant proteins. Enrichment strategies are therefore needed to increase proteome depth without introducing excessive variability, cost, or workflow complexity. The Nanotrap® Protein Enrichment Affinity Kit (PEAK) - Discovery uses magnetic hydrogel particles to selectively enrich proteins from plasma, improving access to low-abundance regions of the proteome while remaining compatible with standard digestion workflows and modern LC–MS/MS platforms. In this study, we evaluated the Nanotrap® PEAK Discovery workflow for proteome depth and reproducibility in human plasma, compared with unenriched samples and alternative commercial enrichment kits, using a standardized digestion protocol and dia-PASEF® analysis on a Bruker timsTOF HT, with a focus on depth, reproducibility, and cost efficiency. Poster presented at the US HUPO 2026 Conference. POSTER SKU 34XXX Literature # PL-PO31526

Article link: https://link.springer.com/article/10.1186/s41043-026-01253-6 Abstract Mass gatherings increase the risk of infectious disease transmission, particularly when healthcare systems are overstretched and underfunded. Wastewater and environmental surveillance (WES) offer a real-time, non-invasive method for monitoring pathogen circulation at the population level. During Uganda’s 2025 Martyrs’ Day pilgrimage, which drew over three million people, the Ministry of Health used WES to identify and respond to health threats. Results All sacred water sources and National Water and Sewage Corporation (NWSC) stand posts remained pathogen-free, and some pilgrims were observed drinking from them. In contrast, wastewater and stagnant surface water harbored multiple pathogens, predominantly non-O1/O139 Vibrio cholerae (36.4%) and Shigella spp. (31.8%), and Rotavirus A and Enterovirus (22.7% each). Notably, on Day 1, the detection of Salmonella spp. and Shigella spp. in a stagnant pool two meters from the Catholic Sacred Martyrs’ Lake prompted immediate drainage and chlorination. On the same day, the identification of multiple enteric pathogens in Anglican Septic Tank 2, located beneath a food-vending zone, prompted septic tank emptying, vendor relocation, and strict food safety enforcement. These findings also triggered rapid WASH upgrades, multilingual community risk communication, and deployment of on-site clinical screening posts. Pathogen diversity peaked on Day 4 (June 3, Martyrs’ Day), with the first detections of SARS-CoV-2 , Mpox virus, Rotavirus C , and RSV. Discussion This study demonstrates the first real-time use of WES to guide public health action during a major mass gathering in Sub-Saharan Africa. The detection of multiple pathogens, mapped by site and time, demonstrated the utility of WES as an early-warning indicator for mass gatherings. The site-specific data enabled rapid interventions, including Water, Sanitation, and Hygiene (WASH) infrastructure upgrades, draining stagnant pools, relocating food vendors, and on-site clinical screening, which likely reduced outbreak risks. These results show how WES can strengthen surveillance and support proactive public health responses at mass gatherings. Conclusion This first real-time WES deployment during a Sub-Saharan mass gathering demonstrates its value for early detection, rapid response, and multi-pathogen surveillance. The effective use of surveillance data to trigger coordinated, multi-agency interventions underscores WES as a vital component of mass-gathering preparedness within global health security frameworks. Nsawotebba, A., Nabadda, S., Hull, N. et al.  Real-time public health interventions driven by wastewater and environmental surveillance during Uganda’s 2025 martyrs day mass gathering. J Health Popul Nutr  (2026). https://doi.org/10.1186/s41043-026-01253-6

Science of The Total Environment, June 2023 " Unveiling indicator, enteric, and respiratory viruses in aircraft lavatory wastewater using adsorption-extraction and Nanotrap® Microbiome A Particles workflows " Abstract: The effective detection of viruses in aircraft wastewater is crucial to establish surveillance programs for monitoring virus spread via aircraft passengers. This study aimed to compare the performance of two virus concentration workflows, adsorption-extraction (AE) and Nanotrap® Microbiome A Particles (NMAP), in detecting the prevalence and concentrations of 15 endogenous viruses including ssDNA, dsDNA, ssRNA in 24 aircraft lavatory wastewater samples. The viruses tested include two indicator viruses, four enteric viruses, and nine respiratory viruses. The results showed that cross-assembly phage (crAssphage), human polyomavirus (HPyV), rhinovirus A (RhV A), and rhinovirus B (RhV B) were detected in all wastewater samples using both workflows. However, enterovirus (EV), human norovirus (HNoV GII), human adenovirus (HAdV), bocavirus (BoV), parechovirus (PeV), epstein-barr virus (EBV), influenza A virus (IAV), and respiratory syncytial virus B (RsV B) were infrequently detected by both workflows, and hepatitis A virus (HAV), influenza B virus (IBV), and respiratory syncytial virus B (RsV A) were not detected in any samples. The NMAP workflow had greater detection rates of RNA viruses (EV, PeV, and RsV B) than the AE workflow, while the AE workflow had greater detection rates of DNA viruses (HAdV, BoV, and EBV) than the NMAP workflow. The concentration of each virus was also analyzed, and the results showed that crAssphage had the highest mean concentration (6.76 log10 GC/12.5 mL) followed by HPyV (5.46 log10 GC/12.5 mL using the AE workflow, while the mean concentrations of enteric and respiratory viruses ranged from 2.48 to 3.63 log10 GC/12.5 mL. Using the NMAP workflow, the mean concentration of crAssphage was 5.18 log10 GC/12.5 mL and the mean concentration of HPyV was 4.20 log10 GC/12.5 mL, while mean concentrations of enteric and respiratory viruses ranged from 2.55 to 3.74 log10 GC/12.5 mL. Significantly higher (p < 0.05) mean concentrations of crAssphage and HPyV were observed when employing the AE workflow in comparison to the NMAP workflow. Conversely, the NMAP workflow yielded significantly greater (p < 0.05) concentrations of RhV A, and RhV B compared to the AE workflow. The findings of this study can aid in the selection of an appropriate concentration workflow for virus surveillance studies and contribute to the development of efficient and reliable virus detection methods.

In this study, we demonstrate that the Nanotrap® Protein Enrichment Affinity Kit (PEAK) significantly reduces the levels of albumin in human plasma samples, as measured by LC-MS/MS. Figure Description: MaxLFQ intensity profiles for albumin across all Nanotrap® PEAK enrichment methods versus unenriched samples. Nanotrap PEAK-enriched samples consistently yielded lower albumin intensity across different LC gradient lengths. This demonstrates the robustness of the Nanotrap PEAK workflows in reducing albumin and enhancing plasma proteome accessibility. TECH NOTE SKU # 34XXX Lit. # PL-TN31440

The Driscoll Lab at West Virginia University uses genomics and bioinformatics to track disease agents and understand how they originate and spread from a One Health perspective. The laboratory processes environmental water samples from wastewater, surface water, and large-scale event wastewater on a statewide basis. The main laboratory is located at the West Virginia University campus, but they also have a mobile laboratory for onsite sample preparation, concentration, and extraction, enabling them to process samples much faster. The lab processes approximately 30 samples per week and is currently testing for SARS-CoV-2, RSV, Flu A, Flu B, and norovirus using both a high-throughput automated system and sequencing. The West Virginia University Environmental Water Surveillance team with their mobile lab. CUSTOMER ADVANCE SKU # 44XXX, 65XXX, 10XXX Lit. # PL-CS31371

The Translational Research Laboratory, which is embedded within the Belfer Center of Applied Cancer Science at Dana-Farber Cancer Institute researches and clinically tests critical unmet needs in the monitoring of oncology treatment from blood and other routinely clinically accessible tissue not addressed by routine pathology. They track patient response to targeted therapies through minimally invasive sampling of circulating tumor cell-free DNA. Early detection of emerging resistance informs clinicians about changes in tumor phenotypes. CUSTOMER ADVANCE SKU # 77XXX Lit. # PL-CS31381

Delaware Public Health Lab’s (DPHL) wastewater surveillance testing is using a predictive method to monitor disease for a more rapid public health response for the entire state of Delaware. Currently, the lab is running 35 wastewater samples per week to detect SARS-CoV-2, influenza virus A and B, mpox, and norovirus. They are planning to add Candida auris to their testing library in the near future. CUSTOMER ADVANCE SKU # 44XXX, 65XXX, 10XXX Lit. # PL-CS31397

The UC Davis Proteomics Core lab offers state-of-the-art LC-MS/MS analysis, including protein identification, proteomics profiling, targeted proteomics, and post-translational modification analysis, for both on- and off-campus clients. Samples run include plasma/serum, tissues, cell culture/pellets, plant material, powder, and more. CUSTOMER ADVANCE SKU # 34XXX Lit. # PL-CS31510

Article Link : https://rdcu.be/e011L Abstract: Wastewater-based surveillance offers a cost-effective, population-level complement to clinical testing for early detection of infectious disease outbreaks; however, its adoption in low- and middle-income countries remains limited. We conducted a study in Kampala, Uganda, to quantify SARS-CoV-2 RNA in wastewater and evaluate its association with reported clinical cases, thereby strengthening community-level surveillance strategies. Methods: From March 2023 to May 2024, 244 wastewater samples were collected weekly from four wastewater treatment plants in the Kampala Metropolitan Area, Uganda. SARS-CoV-2 RNA was quantified by RT-qPCR targeting the ORF1ab, N, and E genes using the Novel Coronavirus (2019-nCoV) Real-Time Multiplex RT-PCR kit, with PMMoV as the process control. Concordance of gene detection was assessed using Cohen’s kappa and the proportion of samples in which all targets were detected. SARS-CoV-2 viral concentrations were reported as log₁₀ genomic copies per 100 mL. Facility-level weekly mean ORF1ab concentrations were aggregated into citywide medians and correlated with clinical positivity, with lead–lag analyses to evaluate spatiotemporal associations. Results: Overall SARS-CoV-2 RNA detection was 88.5%, with higher positivity at the Nakivubo wastewater treatment plant inlets (1 and 2) and the Naalya wastewater stabilization pond (both 93.4%) than at the Bugolobi fecal sludge treatment plant (78.7%). All 3 gene targets were detected in 66.4% of samples, with stronger concordance between ORF1ab and E than between ORF1ab and N (κ = 0.68), and facility-specific variability in three-gene detection ranged from 57.4% to 70.5%. Wastewater viral dynamics were characterized by episodic surges rather than sustained peaks, with ORF1ab concentrations ranging from 2.97 to 11.87 log₁₀ GC/100 mL. While same-week wastewater–clinical correlations were weak, lead–lag analysis showed wastewater signals preceded clinical positivity by 2–5 weeks, with the strongest association at a 4-week lead. Conclusion: WBS provided early warning of SARS-CoV-2 transmission in Kampala, with clinical positivity preceded by up to 1 month. These findings support the integration of WBS into routine surveillance to enhance outbreak preparedness and response, particularly in resource-limited settings, and to inform public health decision-making. Besides COVID-19, WBS can also track multiple infectious diseases by detecting covert transmission patterns and predicting clinical trends. Nsawotebba, A., Nabadda, S., Ssewanyana, I. et al. Wastewater-based surveillance as a proactive public health tool: insights from SARS-CoV-2 monitoring in Kampala, Uganda (2023–2024). BMC Public Health (2026). https://doi.org/10.1186/s12889-026-26267-x

Quantitative and discovery plasma proteomics requires workflows that maximize protein identifications while minimizing variability and cost. The Nanotrap® Protein Enrichment Affinity Discovery Kit (Nanotrap® Discovery Kit) delivers highly reproducible, deep proteome coverage while reducing per-sample cost compared to other enrichment kits. In This Experiment We evaluated whether the manual Nanotrap Discovery Kit enhances proteome coverage and depth while improving workflow reproducibility in human plasma samples compared to two alternative commercial enrichment kits and unenriched plasma using a standard digestion workflow and Bruker timsTOF HT (dia-PASEF®) analysis.   TECH NOTE SKU # 34XXX Lit. # PL-TN31481

Nanotrap® Microbiome Particles are an affinity-bait-based capture system with afinite binding capacity. In complex matrices such as wastewater, the binding is also dependent on the sample matrix, and recovery does not scale uniformly with increasing affinity baits on Nanotrap Particle surfaces. 1  Binding analyses with protein analytes have shown complex changes in recovery based on target accessibility and interaction dynamics with hydrogel particles, rather than simple saturation dynamics. 1   In this study, the interplay of different spikedin organisms was analyzed to determine the effect of varying concentrations of microbes on the detection of other microbial targets within a wastewater matrix. The effect of different background viral and bacterial concentrations were analyzed for patterns that show a bias associated with microbial concentrations. POSTER SKU 44XXX Literature # WW-PO31518