Vector-borne diseases, including yellow fever, Zika, chikungunya, West Nile, and dengue, are posing increasing health risks globally.(1) There is a need for a simple and effective workflow that can be used with wastewater samples to capture and concentrate multiple microbes from a single sample. This experiment demonstrates that the Nanotrap® Microbiome Workflow effectively captures and concentrates low-abundance, vector-borne disease microbes from a single wastewater sample. TECHNICAL NOTE: SKU 44XXX Literature #   WW-TN31413

Here we introduce a new sample preparation tool for plasma-based proteomics that is simple, easy-to-use, and versatile–Nanotrap® Protein Enrichment Affinity Kits. Nanotrap Protein Enrichment Affinity Kits use the Nanotrap magnetic hydrogel particle technology to capture and concentrate low abundance, low molecular weight proteins and peptides while simultaneously excluding higher molecular weight proteins. In this application note, we demonstrate how to use Nanotrap Protein Enrichment Kits to manually process plasma samples collected in K2EDTA blood collection tubes. We compare the number of unique protein identifications obtained from a plasma sample using different Nanotrap Protein Particle workflows, as compared to the same plasma sample processed without using the Nanotrap Protein Enrichment Kit. We also compare the overlap of unique protein identifications for these different workflows. APPLICATION NOTE SKU 34XXX Lit # PL-AN31387

Tuberculosis (TB) causes around 1.4 million deaths annually; earlier detection from complex samples like sputum can enable improved patient outcomes and treatment options.(1,2) Traditional methods like culture are slow and labor-intensive. While alternative molecular testing approaches like qPCR and sequencing are faster, they are hindered by inefficient sample preparation methods and the inhibitory nature of the sputum sample matrix. This study addresses these challenges by using Nanotrap® Microbiome B Particles to enhance Mycobacterium capture and concentration from sputum, offering a novel approach for TB detection. TECHNICAL NOTE: SKU 65XXX Literature #   WW-TN31420

To better understand and characterize the limitations of detection influenza A in wastewater samples, this study evaluated an enhanced workflow combining Nanotrap® Microbiome A Particles for viral enrichment, the Monarch® Mag Viral DNA/RNA Extraction kit with and without a DNase treatment step, and library preparation using the NEBNext® Flu A Integrated Indexing Primer Module protocol, followed by Oxford Nanopore Technologies sequencing. This protocol integrates targeted cDNA synthesis and native barcoding to enable same-day, whole-genome sequencing of influenza A viruses from complex wastewater matrices. The goal of this work was to assess genome coverage across several wastewater samples, evaluate the impact of DNase treatment on sequencing performance, and demonstrate a scalable, high-throughput solution for near real-time influenza surveillance. APPLICATION NOTE: SKU 44XXX Literature #   WW-AN31471

Wastewater surveillance is a critical tool for monitoring infectious diseases like COVID-19 at the community level.¹ As the virus evolves, with variants differing in transmissibility and virulence, tracking these changes is vital for public health. While quantitative PCR is the gold standard for detection and quantification, it typically can’t differentiate among many variants. In contrast, whole-genome sequencing (WGS) provides comprehensive data but is often too complex and resource-intensive for routine wastewater testing.² To address this, we developed a customizable digital PCR (dPCR)-based genotyping method for detecting SARS-CoV-2 variants in wastewater.³ This approach enables rapid, cost-effective screening for specific mutations, capturing both known and emerging variants. We compared dPCR genotyping to WGS using the same elution from each sample and applied the method to wastewater collected across Illinois (Oct 2023–Apr 2024). Results showed high concordance between the two methods. dPCR data aligned with clinical trends and detected early signals of variant rise and decline in near real-time, highlighting its potential as a scalable and timely tool for community-level variant tracking. POSTER: SKU 44XXX SKU 10XXX Literature # WW-PO31458

In this poster, see how the integration of the Nanotrap® Protein Enrichment Affinity Kit (PEAK), when paired with different digestion workflows, yielded substantial improvements in proteome depth compared to unenriched controls. Unique protein identifications using the Nanotrap PEAK workflow with each digestion kit—Pierce, PreOmics iST, and Thermo Scientific SMART Digest— show consistent improvement over neat plasma samples. Additionally, learn how the Gel-based evaluation via SYPRO Ruby staining confirmed the robust exclusion of the 65 kDa albumin band by Nanotrap® Protein A Particles while preserving a diverse range of protein profiles. POSTER: SKU 34XXX Literature #   PL-PO31473

In this study, the Nanotrap® Protein Enrichment Affinity Kit (PEAK) was compared to a magnetic, protein-binding bead-based enrichment kit. Three different healthy human plasma samples were processed using several different Nanotrap® PEAK methods, including the Combined Particle Method, the 2-Particle Method, and the 3-Particle Method.(1) After Nanotrap PEAK enrichment, each sample was digested, cleaned up, and analyzed using LC-MS/MS. Each of the three samples was also processed using off-the-shelf kits for protein enrichment, digestion, and clean-up, and was analyzed using the same settings on the LC-MS/MS. The samples were also processed without protein enrichment as a neat sample. Neat samples were digested, cleaned up, and analyzed using LC-MS/MS. All three of the Nanotrap PEAK methods resulted in more unique protein identifications than the competitor kit’s method for all plasma samples. APPLICATION NOTE SKU 34XXX Lit # PL-AN31399

Wastewater surveillance has become a vital tool for monitoring infectious diseases like COVID-19 at the community level.(1) As microbes continue to mutate, giving rise to variants with differing transmissibility and virulence, tracking the emergence and prevalence of these variants has become a critical component of wastewater-based monitoring. Although PCR-based methods are the gold standard for pathogen detection and quantification, they are generally not designed to distinguish among a broad range of variants. Meanwhile, genomic sequencing—while comprehensive—is often too complex, time-consuming, and resource-intensive for many wastewater testing laboratories.(2) In this study, we developed a customizable digital PCR (dPCR)-based genotyping approach to detect SARS-CoV-2 variants in wastewater.(3) This method provides a rapid and cost-effective way to screen for specific variants, enabling detection of both known and emerging variants beyond predefined markers. We also built a streamlined data analysis pipeline and integrated the results into a public-facing dashboard to deliver real-time insights alongside clinical and GISAID sequencing data. Results from a year-long surveillance effort across Georgia (April 2023–April 2024) highlight the potential of wastewater-based dPCR genotyping as a scalable, timely, and community-representative approach for tracking SARS-CoV-2 variants. POSTER SKU 44XXX

In this study, we demonstrate protein enrichment from human urine samples using the Nanotrap® Protein Enrichment Affinity Kit (PEAK). We processed 1,000 μL each of three different healthy human urine samples using several different manual Nanotrap® PEAK methods, including the Combined Particle Method, the 1-Particle Method, the 2-Particle Method, and the 3-Particle Method.(1) After Nanotrap PEAK enrichment, each sample was digested, cleaned up, and analyzed using LC-MS/MS. Each of the three samples was also processed without protein enrichment as a neat sample. SKU # 34XXX Literature # UR-TN31401

In this study, we demonstrate that the Nanotrap® Protein Enrichment Affinity Kit (PEAK) is compatible with human serum for proteomic analysis. SKU # 34XXX Literature # SR-TN31427

In this study, we demonstrate that the Nanotrap® Protein Enrichment Affinity Kit (PEAK) is compatible with Streck Protein Plus BCT™ for proteomic analysis of human plasma. SKU # 34XXX Literature # PL-TN31428

Abstract Objectives: The growing threat of emerging infectious diseases necessitates proactive genomic surveillance, particularly, in regions with limited resources and low levels of existing reporting. This study highlights the implementation of a comprehensive genomic surveillance program at the Kigali International Airport and explores the utility of a dual-sample strategy leveraging environmental aircraft wastewater and pooled nasal swab sample types for comprehensive detection and characterization of SARS-CoV-2 lineages being imported into Rwanda. Methods: Using a combined pooled nasal swab and aircraft wastewater sampling approach resulted in complementary insights in terms of geographic coverage, positivity, and variant characterization. Results: Mutational profiling in source pooled nasal swabs and aircraft wastewater sample data revealed dynamic shifts in mutation prevalence that corresponded with global patterns. Emerging variant JN.1 was detected early in nasal swab data, demonstrating the power of using genomic surveillance as an early warning system. Conclusions: These results support the feasibility of pathogen surveillance in high-traffic settings and may help drive interest in expanding programs to include pathogens beyond SARS-CoV-2. SKU # 44XXX Misbah Gashegu, Raissa Muvunyi, Jean Pierre Musabyimana, Esperance Umumararungu, Laetitia Irankunda, Chantal Mutezemariya, Arlene Uwituze, Nelson Gahima, John Rwabuhihi, Jean Claude Mugisha, Ayman Ahmed, Noel Gahamanyi, Leon Mutesa, Cecilia A. Prator, Elizabeth A. Landis, Casandra W. Philipson, Nicole Bohme Carnegie, Albert Tuyishime, Isabelle Mukagatare, Noella Bigirimana, Claude Mambo Muvunyi, Early detection of SARS-CoV-2 variants using genomic surveillance: insights from aircraft wastewater and nasal swabs at Kigali International Airport, Rwanda, IJID Regions, Volume 16, 2025, 100678, ISSN 2772-7076, https://doi.org/10.1016/j.ijregi.2025.100678 . (https://www.sciencedirect.com/science/article/pii/S2772707625001134)