Professor Benjamin Callahan to receive the ASM’s Microbiome Data Prize for 2023

Benjamin Callahan, BRC member and Associate Professor of Department of Population Health and Pathobiology, has been selected to receive the 2023 Microbiome Data Prize by the American Society for Microbiology. Dr. Callahan is widely known for the development of the DADA2 package for sample inference from amplicon data, which has received over 12.000 citations. More generally, he has been instrumental in developing standard and reproducible workflows for handling metagenomic data.

Callahan joined the faculty of North Carolina State University in Jan. 2017 as a Chancellor’s Faculty Excellence Program cluster hire in microbiomes and complex microbial communities. Callahan’s research program at N.C. State focuses on microbomes and the high-throughput methods used to characterize them, in particular marker-gene and metagenomic sequencing. He develops new statistical and bioinformatic methods to better characterize microbial communities from high-throughput biological data. Callahan uses those methods to study important problems, such as the relationship between the maternal microbiome and preterm birth and the barriers to reproducibility and interoperability between microbiome measurements made in different laboratories. Callahan and his group also develop and support software used by the wider microbiome research community in a wide variety of applications.

Additional details about DADA2 and Dr. Callahan’s research are described here: https://asm.org/Articles/2022/October/Advancing-Microbiome-Data-Analysis-with-Benjamin-C

David Reif named to the U.S. Environmental Protection Agency (EPA) Science Advisory Committee on Chemicals (SACC)

David Reif was named to the U.S. Environmental Protection Agency (EPA) Science Advisory Committee on Chemicals (SACC) for a four-year term by Administrator Michael Regan. The Science Advisory Committee on Chemicals provides independent scientific advice, information and recommendations to the EPA Office of Pollution Prevention and Toxics on the scientific basis for risk assessments, methodologies and pollution prevention measures or approaches. Its major objectives are to provide expert advice and recommendations to the EPA on risk assessments, models, tools, guidance documents, chemical category documents and other chemical assessment and pollution prevention products as deemed appropriate.

The COVID-19 Pandemic Vulnerability Index (PVI)

The COVID-19 Pandemic Vulnerability Index (PVI)

Dr. David Reif has led teams at North Carolina State University, NIEHS, and Texas A&M University in developing the Pandemic Vulnerability Index (PVI) dashboard, which offers a view and real-time analysis of county-level U.S. data on the coronavirus pandemic. “The dashboard helps officials allocate resources and update responses, as well as providing both county-level and a nationwide overview of various statistics” explained Dr. Reif.  The team developed risk profiles, called PVI scorecards, are available for every county in the United States. The resource has now been added to the COVID Data Tracker resources curated on the U.S. Centers for Disease Control and Prevention website

https://covid.cdc.gov/covid-data-tracker/#pandemic-vulnerability-index), and was featured in the Environmental Factor (https://factor.niehs.nih.gov/2021/2/feature/1-feature-pandemic/index.htm)

The original publication appeared  in Environmental Health Perspectives (https://ehp.niehs.nih.gov/doi/10.1289/EHP8690).

Additional NC State co-authors include Dr. Yi-Hui Zhou, Dr. Fred A. Wright, and Kuncheng Song.

Collaboration points to potential dangers of energy drinks

Collaboration points to potential dangers of energy drinks

Dr. Yi-Hui Zhou and colleagues reported on the potential dangers of popular energy drinks in the March 2021 issue of Food and Chemical Toxicology. The study, led by Dr. Ivan Rusyn, a professor in the Veterinary Integrative Biosciences at Texas A&M University, showed that cardiomyocytes – human heart cells grown in a laboratory – exposed to some energy drinks showed an increased beat rate and other factors affecting cardiac function. Dr. Zhou used complex patterns from mass spectrometry to show that certain chemical profiles from the energy drink constituents were associated with aspects such as QT prolongation,  which is associated with serious human heart conditions. “This was a great collaboration showing the power of machine learning methods to learn features of the data that have direct relevance to human health,” explained Dr. Zhou. The project has gained considerable media attention, due to the popularity of energy drinks, which has a $61 billion worldwide market. “Many consumers don’t realize that energy drinks are marketed as regular beverages or dietary supplements, and as such don’t really undergo extensive safety testing” said Dr. Zhou.  “Some ingredients may be available from natural sources but still have worrisome effects on heart function.  Further research should be performed, as some people, even children, consume these drinks every day.”

Link to the article : https://www.sciencedirect.com/science/article/abs/pii/S0278691521000132

Other NC State authors include Fred A. Wright and Erin Baker.

4D- quantitative structure–activity relationship modeling: making a comeback

Predictive Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential methodology for rapidly assessing various properties of chemicals. The vast majority of these QSAR models utilize numerical descriptors derived from the two- and/or three-dimensional structures of molecules. However, the conformation-dependent characteristics of flexible molecules and their dynamic interactions with biological target(s) is/are not encoded by these descriptors, leading to limited prediction performances and reduced interpretability. 2D/3D QSAR models are successful for virtual screening, but typically suffer at lead optimization stages. That is why conformation-dependent 4D-QSAR modeling methods were developed two decades ago. However, these methods have always suffered from the associated computational cost. Recently, 4D-QSAR has been experiencing a significant come-back due to rapid advances in GPU-accelerated molecular dynamic simulations and modern machine learning techniques.

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Adipocytes as Anticancer Drug Delivery Depot

Tumor-associated adipocytes promote tumor growth by providing energy and causing chronic inflammation. Here, we have exploited the lipid metabolism to engineer adipocytes that serve as a depot to deliver cancer therapeutics at the tumor site. Rumenic acid (RA), as an anticancer fatty acid, and a doxorubicin prodrug (pDox) with a reactive oxygen species (ROS)-cleavable linker, are encapsulated in adipocytes to deliver therapeutics in a tumor-specific bioresponsive manner. After intratumoral or postsurgical administration, lipolysis releases the RA and pDox that is activated by intracellular ROS-responsive conversion, subsequently promoting antitumor efficacy. Furthermore, downregulation of PD-L1 expression is observed in tumor cells, favoring the emergence of CD4+ and CD8+ T cell-mediated immune responses.

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USDA/NIFA grants awarded to faculty members Drs. David Rasmussen & Benjamin Callahan

Two faculty members, Dr. David Rasmussen and Dr. Benjamin Callahan, were awarded USDA NIFA grants through a new program called FACT: Food and Agricultural Cyberinformatics and Tools Initiative.

Dr. Rasmussen’s project is called, “Next Generation Spatial Epidemiology for Tracking the Spread of Plant Pathogens”.  The main goal is: “To develop the next generation of phylogenetic tools for tracking the spread of plant pathogens ranging from viruses to fungi through complex agricultural landscapes. Since many of these pathogens undergo occasional recombination, another goal is to use information about recombination events across pathogen genomes to identify the spatial location of historical recombination events and the geographic source of particular genes involved in pathogenesis.”


Dr. Callahan’s project is called, “Rapid Detection and Tracking of Foodborne Pathogens with Long-read Amplicon Sequencing”. Food-borne pathogens enact substantial harms on the American people in the form of illness, lost productivity, and expenses related to mitigation and regulatory compliance. Surveillance and tracing of foodborne pathogens is a key control strategy, but its efficacy is reduced by the long-times associated with current culture and whole-genome-sequencing approaches. Rapid, accurate and comprehensive pathogen detection would improve the safety and lower the costs of our food supply.

We aim to develop a targeted metagenomics methodology that can rapidly (<24 hrs) and precisely identify a broad range of foodborne pathogens from heterogeneous environmental samples. In order to achieve this, we propose to combine the GenomeTrakr and NCBI RefSeq databases with cutting-edge bioinformatics tools developed by the PD that achieve single-nucleotide resolution from amplicon sequencing data of full-length genes to identify E. coli and Salmonella strains to the serovar level (e.g. E. coli O157:H7 or S. enterica Heidelberg). We will validate the resolution and accuracy of this new methodology in silico, on isolates of various pathogenic serovars, and in environmental samples of various types for which pathogen presence and identity were previously established by standard culture-based methods. Our methodology will be distributed to the broader food safety community as open-source and actively-supported software, alongside extensive documentation of its efficacy and best-practices guidance. Successful completion of this project will yield a powerful, usable, and broad-spectrum pathogen surveillance technique that will improve food safety by detecting foodborne pathogens before they reach consumers, and by rapidly tracing outbreaks to their source.”

“A Class Approach to Hazard Assessment of Organohalogen Flame Retardants”

A new report from the National Academies of Sciences, Engineering, and Medicine offers guidance to the Consumer Product Safety Commission (CPSC) on how to conduct a hazard assessment of nonpolymeric, additive organohalogen flame retardants (OFRs), which are used in some consumer products.

OFRs cannot be treated as a single class for hazard assessment, the report says, but they can be divided into subclasses based on chemical structure, physical and chemical properties, and predicted biologic activity. The report identifies 14 subclasses that CPSC can use to conduct a class-based hazard assessment of OFRs. Such an approach is likely to be more efficient and less costly than the traditional approach of evaluating each chemical individually, the report notes.

There is mounting evidence that many flame retardants are associated with adverse human health effects, and some flame retardants have been banned, restricted, or voluntarily phased out of use. A coalition of organizations and individuals petitioned CPSC to initiate regulatory action to ban use of OFRs in four product categories: infant, toddler, or children’s products; upholstered furniture; mattresses; and plastic electronic casings. The petitioners argued that the entire chemical class is toxic and poses a risk to consumers.

CPSC voted to grant the petition, but in order to decide whether a ban should be enacted, the agency must first conduct a hazard assessment to determine whether a chemical is toxic. CPSC asked the National Academies for guidance on how to conduct the hazard assessment for OFRs as a chemical class.

The National Academies study committee first conducted an analysis to determine whether OFRs can be treated as a single class. This involved identifying known OFRs and other structurally related organohalogen compounds. The committee found that OFRs cannot be distinguished as a single class from these other chemically similar analogues. In addition, OFRs do not have a common chemical structure or predicted biologic activity and therefore cannot be treated as a single class.

However, an approach that uses subclasses to assess the chemicals is scientifically justifiable, the committee determined.  The report outlines a process for assessing the toxicity of the 14 identified subclasses and identifies four scenarios that might occur, depending on how much data is available for the chemicals in a subclass. The report also uses two subclasses to illustrate how the proposed approach to the hazard assessment would work.

A multidisciplinary group will be needed to execute the hazard assessment, the report says. Needed expertise includes cheminformatics, computational chemistry, computational toxicology, traditional and modern toxicology, epidemiology, and risk assessment. Furthermore, integrating the evidence at various steps will require expert judgment, and policy decisions involving value judgments – for example, about what health endpoints to investigate and how much uncertainty is acceptable – will be needed to complete the assessment.

The study — undertaken by the Committee to Develop a Scoping Plan to Assess the Hazards of Organohalogen Flame Retardants — was sponsored by the Consumer Product Safety Commission. The National Academies are private, nonprofit institutions that provide independent, objective analysis and advice to the nation to solve complex problems and inform public policy decisions related to science, technology, and medicine. They operate under an 1863 congressional charter to the National Academy of Sciences, signed by President Lincoln. For more information, visit nationalacademies.org.


Visit the original press release here

System toxicological approaches to define and predict the toxicityofPerand Polyfluoroalkyl Substances

System toxicological approaches to define and predict the toxicityofPerand Polyfluoroalkyl Substances

This project will assess the toxicity of a large collection of volatile and non-volatile PFASs (Per and Polyfluroalkyl Substances). The research results will increase the knowledgebase of toxicity profiles for a large collection of PFASs, covering a wide variety of toxicological endpoints, and may provide key scientific information for prioritizing different types of PFAS for effective and efficient risk assessment and management.

Objective:

1: Study the toxicity of a large collection of volatile and non-volatile PFASs and PFAS mixtures with the zebrafish assay. Hypothesis: PFAS compounds with similar structures will bind to the same biomolecular targets, induce expression of the same or highly overlapping gene sets, and induce similar toxic responses.

2: Conduct developmental immunotoxicity (DIT) studies in mice. Hypotheses: Developmental exposure to PFASs will compromise antigen-specific antibody responses (a measure of adaptive immunity) and natural killer cell cytotoxicity (a measure of innate immunity). Developmental findings in the mouse will accord with developmental findings in the zebrafish.

3: Create pharmacokinetic models that can explain and predict the concentrations of PFASs in the organs of mice and adult zebrafish as a function of exposure dose and chemical structure. Hypotheses: The bioaccumulation and internal distribution of PFASs depend on passive diffusion, transporter-mediated membrane uptake and efflux, and protein binding. The interaction of PFASs with proteins and membranes will depend on i) the presence of polar or charged functional groups and on ii) the length of the linear fluorinated alkyl chain.

Approach:

Expose embryonic zebrafish to 100 PFASs and assess them for adverse phenotypic and behavioral effects. Identify the gene expression changes associated with the observed effects. Expose juvenile zebrafish to PFASs and assess them for adverse behavioral effects. Expose mice to PFASs that are toxic to embryonic zebrafish and assess them for developmental immunotoxicity. Create pharmacokinetic models that can explain and predict the concentrations of PFASs in the organs of mice and adult zebrafish as a function of exposure dose and chemical structure.

Expected Results:

The project will increase by 400% the number of PFASs for which the research community has tested for toxicity in vivo. It will help EPA to identify toxic PFASs that require prioritization for risk management. The models developed will improve hazard and risk assessment of many PFASs and thereby improve EPA’s ability to protect human health and the environment. Over the long term, the project could enable researchers to determine the toxicity of PFASs without animal testing, solely on the basis of chemical structure. It could help industries worldwide to understand which PFASs are most toxic and to select or develop non-toxic materials that achieve the same useful results.

For more details, please see the EPA website:

https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/display.abstractDetail/abstract/10950/report/0

Five Questions with Fred Wright

NC State’s Chancellor’s Faculty Excellence Program showcases the university’s commitment to interdisciplinary excellence and field-leading faculty. Cluster faculty turn research into real-world solutions while providing students with well-rounded experiential education opportunities.

We spoke with Fred Wright, a member of the Bioinformatics cluster and director of the Bioinformatics Research Center, about his research and the impact of interdisciplinarity at NC State.


What is your role within the Bioinformatics cluster and what are your primary research interests?

I was hired as a member of the Bioinformatics cluster in 2013 — partly because of my research, but also to be the director of the Bioinformatics Research Center. This interdisciplinary research center, established in 2000, brings faculty from different colleges and departments together who have complementary interests in using quantitative reasoning to solve biological problems. We have faculty from departments like biological sciences, statistics and chemistry who represent interdisciplinary work, but physically are in the Ricks Hall third floor facility. The idea is to conduct research, pursue grants and further our work by virtue of being close together physically.

My own work covers a number of areas in statistical genetics. Most of my research concerns gene mapping or genomics and relating those to diseases in humans or model systems such as mice. I collaborate with others to gather what we call “omics data,” which could be DNA in mice or humans, or it could be what’s known as expression data, which represents the degree to which genes are turned on and turned off, and that can vary by tissue and vary over the lifespan of an individual.

What do you hope to achieve through the research being conducted in the bioinformatics cluster and the Bioinformatics Research Center?

The cluster did a lot to strengthen environmental bioinformatics instantly. Professors David Reif, Denis Fourches and I spend part of our time working on the application of genomics to toxicology, as well as chemical informatics. This is an important emerging research area that combines traditional toxicology with new omics methods. The Triangle area is quite strong in this area, even though there are relatively few people working in this combined field. To have three people in that one cluster automatically made us much stronger as an institution in bioinformatics. In addition to adding to the original strengths of statistical genetics within the center, enhanced environmental work was something the cluster was able to bring to campus. Additionally, the Bioinformatics cluster builds on existing strengths within the Bioinformatics Research Center. Our other cluster member, Dahlia Nielsen, represents strengths in statistical genetics, combining a deep understanding of biology and statistical genetics with the most modern technology.

What is your favorite part of being a researcher?

It is cliche to say that we like the excitement of discovery, but it is true. Just sitting at a computer and suddenly seeing a pattern in data that no one had ever noticed before is something that researchers have to live for, because otherwise, why are you doing that? In my role as director, I get some satisfaction in seeing that we’ve been able to grow, sometimes in the face of difficult funding situations. Much of this, due to the vision of the chancellor and provost, to have this faculty excellence program, has been one of the ways in which we have been able to grow. Helping to steer that and seeing that we’re bringing in excellent people gives me a lot of satisfaction.

How does interdisciplinarity impact both faculty and students?

Research complements training, and traditionally that’s been thought of as something most applicable to graduate students. Increasingly we’re seeing the involvement of undergraduates in research and it is something that has taken hold on other campuses and is starting to take hold here. I’ve had some undergraduates training in our group and there are other faculty involved with the center and with the cluster who are actively engaging undergraduate students.That kind of exposure in the early stages of academic development is certainly good for the students. For us it is an extra set of hands and it helps develop a researcher pipeline. There are quite a few students who remain local or they may go off and get a master’s degree somewhere else and come back here for a Ph.D. All versions of this are very good for us — for the center, the cluster and the institution. We create the research space so that research can thrive and so that students — no matter their eventual career goals — are able to see what it means to generate knowledge.

What is something people may not know about the Bioinformatics cluster or the Bioinformatics Research Center?

We’re very approachable! There are some students who have been trained in biology who may not realize that with a reasonable amount of training — maybe a few months of training in computer languages — they can do something in bioinformatics. There is a startup cost to be able to do interdisciplinary work. You have to understand at least a little bit about multiple disciplines, but it is not necessarily as high a barrier as some people think. We provide formal training opportunities as well as self-taught experiences that can often get people to the point where they understand enough to be able to engage in the process.

Another thing is people don’t realize how many jobs there are in this area in particular. Data science is increasingly something that people are focused on. We have a large number of students who have graduated and gone on to very good positions here in the Triangle and across the nation. Bioinformatics is a bigger area that many students realize.


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