About

Sam Nugen is a Professor at Cornell University in the Department of Food Science. His research group focuses on utilizing synthetic biology and phage-based biosensors to develop novel methods for separating and detecting pathogens from complex matrices such as food and environmental samples. Professor Nugen's work aims to improve food and water safety through innovative biotechnological approaches. He earned his B.S. in Animal Science from the University of Vermont and his M.S. in Food Science from Cornell University. Following his master's degree, he worked as a Research Engineer at Kraft Foods, where he contributed to process engineering for new products. Dr. Nugen then returned to Cornell to complete his doctorate and postdoctoral research in the departments of Food Science and Biological Engineering, respectively. After serving as an Assistant Professor at the University of Massachusetts, Amherst, he joined Cornell's Department of Food Science as an Associate Professor and was promoted to Full Professor in 2021.

Research topics

• Computer Science
• Biology
• Computational biology
• Engineering
• Materials science
• Genetics
• Chemistry
• Biochemistry
• Data science
• Nanotechnology
• World Wide Web
• Combinatorial chemistry

Selected publications

• Scarless One-Tube Genome Assembly via Computationally Optimized Uracil-DNA Glycosylase Reactions

  RSC Chemical Biology · 2026-01-01

  articleOpen accessSenior author

  Synthetic biology enables the creation of systems such as bacteriophage (phage)-based biosensors, leveraging the innate specificity and efficiency of phages to rapidly identify pathogens. However, the current genome assembly and...

  PublisherOA PDFDOI

• Synthetic biology meets diagnostics: Engineering biosensing platforms for rapid and accurate pathogen and viral detection

  Biosensors and Bioelectronics · 2025-09-02 · 4 citations

  review
  PublisherDOI

• <i>Escherichia</i> Phage Ge15, NRG-P0073: Genomic Characterization and Host Range Analysis Against the ECOR Reference Library

  PHAGE · 2025-03-26

  articleOpen accessSenior author

  Background: Genomic sequencing and annotation, morphological characterization, and host range analyses of bacteriophage (phage) isolates are crucial to understanding each phage’s unique set of properties and how they can be utilized as effective tools in medicine, environmental monitoring, biotechnology, and agriculture. In this study, we present the fully annotated genome of viral isolate Escherichia phage Ge15 (GenBank Accession No. PP359696.1), taxonomically identified as unclassified Tequatrovirus, and deposited into our strain collection as sample NRG-P0073. A host range analysis was performed against all 72 isolates of the E. coli Reference (ECOR) library and a selection of Escherichia coli K-12 single-gene knockouts from the Keio collection in an effort to identify the receptor-binding protein. Materials and Methods: Whole genome sequencing, de novo assembly, and evidence-driven annotation using the Center for Phage Technology’s Galaxy and Apollo software were performed on NRG-P0073. Double-agar spot tests were performed against the ECOR library and nine E. coli K-12 knockouts from the Keio collection to evaluate both the permissive and adsorptive host ranges of the phage. Transmission electron microscopy was utilized to elucidate the phage morphology. Results: NRG-P0073 was found to have a 170,913 bp genome, coding for 10 tRNAs, 14 terminators, 259 genes, 249 coding sequences, and a GC content of 35.5%. Double-agar spot tests revealed that NRG-P0073 could adsorb 33 of the 72 strains (45.8%), but only 15 of the 72 strains (20.8%) could complete replication to form distinguishable plaques. All nine of the E. coli K-12 single-gene knockout strains (100%) supported complete phage replication, suggesting that none of the nine evaluated receptors are solely responsible for facilitating the attachment of NRG-P0073 to the host surface. Conclusions: This study presents novel and complete genomic data, characterization, and host range analyses for the newly characterized phage NRG-P0073. Further characterization and analysis are required, including the identification of the E. coli receptor-binding protein responsible for initial host recognition. This study provides a foundation for future studies to understand more about NRG-P0073 and provides data that can be utilized for future machine-learning studies of phages and their host interactions.

  PublisherDOI

• Fusing bacteriophage specificity with MOF nanozyme catalysis to construct an AI-enhanced platform for simultaneous pathogen detection and eradication

  Chemical Engineering Journal · 2025-11-09 · 1 citations

  article
  PublisherDOI

• Gp38 adhesins of Straboviridae phages recognize specific extracellular loops of outer membrane protein receptors

  npj Viruses · 2025-04-25 · 2 citations

  articleOpen access

  Tailed bacteriophages (phages) depend on specific interactions with their host receptors for efficient infection and propagation. Gp38 is a unique receptor-binding protein located at the distal tail of Straboviridae phages characterized by a defined modular, monomeric structure. Here, we demonstrated that the similarity of Gp38 adhesins, encoded by related yet distinct Straboviridae phages belonging to Tequatrovirus, Mosigvirus, and Krischvirus, determines the recognition of receptors such as Tsx, OmpF, and OmpA. For OmpA, experimental and in silico analysis identified specific outer loops protruding from the receptor required for phage infection by interacting with Gp38. Yet, the loops involved are dependent on the adhesin variant. In-depth in silico analysis identified two groups of Gp38 adhesins differentially interacting with OmpA by expressing specific amino acids. This demonstrates that both partners’ diversity affects phage binding and host range. Overall, the phylogeny of Gp38 adhesins can predict receptor binding essential for advancing phage therapy.

  PublisherOA PDFDOI

• Recoded Bacteriophage Genome for Bio-Orthogonal-Enabled Concentration and Detection of <i>E. coli</i> in Drinking Water

  ACS Synthetic Biology · 2025-12-23

  articleOpen accessSenior authorCorresponding

  Modern genome editing methods permit the flexible modification of organisms at the genome level. However, bacteriophages, despite their small genomes, pose unique challenges due to the need to edit during their infection cycle, then select/screen for the modified genomes against a background of the wild type phage. Direct genome synthesis enabled by High-Complexity Golden Gate Assembly (HC-GGA) offers an alternative approach that permits rapid, accurate, and flexible genome modification. Here, we demonstrate HC-GGA’s bacteriophage engineering potential, particularly in addressing the public health challenge of detecting hazardous pathogens and nonpathogenic bacteria as indicators of fecal contamination (indicator organisms) in water supplies. A bacteriophage-based biosensor was developed by recoding the genome to enable in vivo incorporation of the alkyne-modified noncanonical amino acid L-homopropargylglycine into the capsid. The modification enabled a bio-orthogonal cycloaddition reaction with azide-conjugated magnetic nanoparticles resulting in magnetized phages which were able to bind, capture, and concentrate their host E. coli. In parallel, the engineered phage expressed luciferase during infection, allowing detection of E. coli at concentrations below 10 CFU per 100 mL in drinking water samples. The approach significantly reduces assay time and cost associated with such assays, particularly in field-based applications, thereby illustrating the practical benefits of synthetic biology in environmental monitoring and public health initiatives.

  PublisherDOI

• NRG-P0074 Viral Sample RU1 from Unclassified <i>Mosigvirus</i> Genomic Characterization and Host Range Analysis

  PHAGE · 2025-05-16

  articleOpen accessSenior author

  Background: Machine learning models for phage–host range prediction and design require comprehensive training data on phage genomes and host ranges to predict phage–host interactions effectively. Materials and Methods: This study characterizes phage sample NRG-P0074 viral sample RU1 from unclassified Mosigvirus , originally isolated by the Betty Kutter. The complete genome of NRG-P0074 was sequenced, annotated, and analyzed using various bioinformatic tools. Host range analysis was conducted using the Escherichia coli Reference (ECOR) Library and nine Escherichia coli (E. coli) K12 strains (Keio Knockout Collection) with single nonessential gene deletions. Results: The genome of NRG-P0074 spans 168,357 base pairs with a guanine-cytosine (GC) content of 37.5%. NRG-P0074 exhibited permissiveness in 15.28% of the ECOR isolates and all 9 Keio knockout strains. Comparative genomic analysis revealed that NRG-P0074 is closely related to E. coli phage a20. Its genome is comprised of 270 coding sequences, 153 known genes, 16 terminators, 3 ribosomal-binding sites, 0 tRNAs, and 117 hypothetical proteins. Conclusions: This research provides valuable data for developing machine learning models to predict phage–host interactions, aiding the development of targeted phage therapies against antibiotic-resistant bacteria.

  PublisherDOI

• Genetic engineering of bacteriophage S16 for Salmonella separation, concentration, and detection

  Analytical and Bioanalytical Chemistry · 2025-05-27 · 2 citations

  articleSenior author
  PublisherDOI

• Bacteriophage-Based Bioanalysis

  Annual Review of Analytical Chemistry · 2024-07-17 · 11 citations

  reviewOpen accessSenior author

  Bacteriophages, which are viral predators of bacteria, have evolved to efficiently recognize, bind, infect, and lyse their host, resulting in the release of tens to hundreds of propagated viruses. These abilities have attracted biosensor developers who have developed new methods to detect bacteria. Recently, several comprehensive reviews have covered many of the advances made regarding the performance of phage-based biosensors. Therefore, in this review, we first describe the landscape of phage-based biosensors and then cover advances in other aspects of phage biology and engineering that can be used to make high-impact contributions to biosensor development. Many of these advances are in fields adjacent to analytical chemistry such as synthetic biology, machine learning, and genetic engineering and will allow those looking to develop phage-based biosensors to start taking alternative approaches, such as a bottom-up design and synthesis of custom phages with the singular task of detecting their host.

  PublisherDOI

• Bacteriophage-Based Sensors, Past and Future

  Elsevier eBooks · 2023-06-17

  book-chapterSenior authorCorresponding
  PublisherDOI

Recent grants

• Phage-Enabled Lab-on-a-Filter for Pathogen Separation, Concentration, and Detection

  NIH · $616k · 2018–2022

• Collaborative Research: Phage-based nanobiosensors for the rapid detection of food and waterborne pathogens

  NSF · $220k · 2017–2021

• Accelerating phage evolution and tools via synthetic biology and machine learning

  NIH · $2.6M · 2019–2026

Frequent coauthors

• Juhong Chen

  Virginia Tech

  54 shared

• Troy Hinkley

  32 shared

• Julie M. Goddard

  Cornell University

  24 shared

• Danhui Wang

  Changsha Hospital for Maternal and Child Health Care

  23 shared

• David A. Sela

  University of Massachusetts Amherst

  22 shared

• Vincent M. Rotello

  University of Massachusetts Amherst

  19 shared

• Joey N. Talbert

  Iowa State University

  14 shared

• Spencer Garing

  Intellectual Ventures (United States)

  14 shared

Labs

• Nugen Research GroupPI