Paper published on viable bacteria around hospital windows!

In a 2019 collaboration between the Biology and the Built Environment Center at the University of Oregon and the Oregon Health & Sciences University, we sampled various window surfaces from patient rooms in a hospital ward. We characterized the viable bacterial community located on these surfaces, and investigated the association of relative light exposure of the surface (in direct light or not), the cardinal direction of the room (and roughly the amount of total light exposure in a day), and proximity of the patient room to the nurses’ station (which has higher occupancy and traffic).

This image has an empty alt attribute; its file name is figure1.jpg
Figure 1. Floor plan and rendering of a typical patient room at the Oregon Health and Science University hospital. (a) Floor plan of the 13th floor of Kohler Pavilion (13K) at Oregon Health and Science University (OHSU). Red shading indicates the rooms that were sampled between 10:00 a.m. and 11:00 a.m. on June 7, 2019 (b) Digital rendering of a typical patient room on OHSU (13K) with the sampling locations indicated by the numbers. The sampled locations were (1) window glass surface, (2) the window frame surface facing into the room at the sill, (3) glazing-side of the window frame at the sill, (4) window-side of the curtain, (5) patient-side of the curtain and, (6) wood-covered air return grille.

The microbial community found in buildings is primarily a reflection of the occupants, and in the case of hospitals, the microbiota may be sourced from patients, staff, or visitors. In addition to leaving microbiota behind, occupants may pick up microorganisms from building surfaces. Most of the time, this continuous exchange of microorganisms between a person and their surroundings is unremarkable and does not raise concerns. But in a hospital setting with immunocompromised patients, these microbial reservoirs may pose a risk.  Window glass, sills, and the surfaces around windows are often forgotten during hospital disinfection protocols, and the microbial communities found there have not previously been examined.

This paper is the first first-authored research paper from a former undergraduate mentee of mine at the University of Oregon; Patrick Horve.

Horve, P.F., Dietz, L., Ishaq, S.L., Kline, J., Fretz, M., Van Den Wymelenberg, K. 2020. Viable bacterial communities on hospital window components in patient rooms. PeerJ 8: e9580. Impact 2.353. Article.

Paper published on soil microbes, climate change, and agriculture!

I’m pleased to announce that an article was published today on soil microbes, climate change, and agriculture! As local climates continue to shift, the dynamics of above- and below-ground associated bio-diversity will also shift, which will impact food production and the need for more sustainable practices. 

This publication is part of a series, from data collected from a long-term farming experiment in Bozeman, MT, led by researchers at Montana State University with whom I have published several times, including:

In this study, cropping system (such as organic or conventional), soil temperature, soil moisture, the diversity and biomass of weed communities, and treatment with Wheat streak mosaic virus were compared as related to the bacterial community in the soil associated with wheat plant roots.

This paper is open-access, which means anyone can read the full paper.

Dryland cropping systems, weed communities, and disease status modulate the effect of climate conditions on wheat soil bacterial communities.

Ishaq, S.L., Seipel, T., Yeoman, C.J., Menalled, F.D. 2020. mSphere DOI: 10.1128/mSphere.00340-20. Article.


Little knowledge exists on how soil bacteria in agricultural settings are impacted by management practices and environmental conditions under current and predicted climate scenarios.  We assessed the impact of soil moisture, soil temperature, weed communities, and disease status on soil bacterial communities between three cropping systems: conventional no-till (CNT) utilizing synthetic pesticides and herbicides, 2) USDA-certified tilled organic (OT), and 3) USDA-certified organic with sheep grazing (OG).  Sampling date within the growing season, and associated soil temperature and moisture, exerted the greatest effect on bacterial communities, followed by cropping system, Wheat streak mosaic virus (WSMV) infection status, and weed community. Soil temperature was negatively correlated with bacterial richness and evenness, while soil moisture was positively correlated with bacterial richness and evennessSoil temperature and soil moisture independently altered soil bacterial community similarity between treatments.  Inoculation of wheat with WSMV altered the associated soil bacteria, and there were interactions between disease status and cropping system, sampling date, and climate conditions, indicating the effect of multiple stressors on bacterial communities in soil.  .  In May and July, cropping system altered the effect of climate change on the bacterial community composition in hotter, and hotter and drier conditions as compared to ambient conditions, in samples not treated with WSMV.  Overall, this study indicates that predicted climate modifications as well as biological stressors play a fundamental role in the impact of cropping systems on soil bacterial communities.

Pilot study published on chemicals and bacteria in house dust.

In October 2017, Dr. Rich Corsi came to visit Oregon for two weeks during a sabbatical from the University of Texas, Austin. During his stay, Rich and I, and other BioBE/ESBL researchers chatted about doing a pilot study that would bring UT’s indoor chemistry work together with BioBE’s indoor microbial work.

Since we began our collaboration in the fall of 2017, only one of the research team is still in their original position (Jeff Kline at ESBL)! Rich Corsi, Ying Xu, and myself have all gone on to faculty positions elsewhere, graduate student Chenyang Bi defended and started a post-doc position, and the two undergrads working with me, Susie Nunez and Samantha Velazquez, graduated and went on to other things! Science collaborations work best when they can stand the test of time and geography. The benefit to everyone moving around is that you are able to hold collaboration meetings in new and exciting places each time.

In addition to the literature review we collaborated on, we eventually did get a research pilot running, and it has now been published in PeerJ!

Accumulation of di-2-ethylhexyl phthalate from polyvinyl chloride flooring into settled house dust and the effect on the bacterial community.

Samantha Velazquez1, Chenyang Bi 2,3, Jeff Kline 1,4, Susie Nunez1, Richard Corsi 3,5, Ying Xu 3,6, Suzanne L. Ishaq1,7*


1 Biology and the Built Environment Center,  University of Oregon, Eugene, OR, 97403

2 Department of Civil Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061 (current)

3 Department of Civil, Architectural and Environmental Engineering, University of Texas, Austin, TX 78712

4 Energy Studies and Buildings Laboratory, University of Oregon, Eugene, OR, 97403

5 Fariborz Maseeh College of Engineering and Computer Science, Portland State University, Portland, OR 97207 (current)

6 Department of Building Science, Tsinghua University, 100084, Beijing, P. R. China (current)

7 School of Food and Agriculture, University of Maine, Orono, ME 04469 (current)


Di-2-ethylhexyl phthalate (DEHP) is a plasticizer used in consumer products and building materials, including polyvinyl chloride flooring material. DEHP adsorbs from material and leaches into soil, water, or dust, and presents an exposure risk to building occupants by inhalation, ingestion, or absorption.  A number of bacterial isolates are demonstrated to degrade DEHP in culture, but bacteria may be susceptible to it as well, thus this study examined the relation of DEHP to bacterial communities in dust.  Polyvinyl chloride flooring was seeded with homogenized house dust and incubated for up to 14 days, and bacterial communities in dust were identified at days 1, 7, and 14 using the V3-V4 regions of the bacterial 16S rRNA gene.  DEHP concentration in dust increased over time, as expected, and bacterial richness and Shannon diversity were negatively correlated with DEHP concentration.  Some sequence variants of Bacillus, Corynebacterium jeddahense, Streptococcus, and Peptoniphilus were relatively more abundant at low concentrations of DEHP, while some Sphingomonas, Chryseobacterium, and a member of the Enterobacteriaceae family were relatively more abundant at higher concentrations.  The built environment is known to host lower microbial diversity and biomass than natural environments, and DEHP or other chemicals indoors may contribute to this paucity.

Paper published on effect of farming systems on soil bacteria!

After several years of bouncing through internal and external review, I’m pleased to announce that the first microbes paper out of the Montana State University Fort Ellis project has been published in Geoderma! The Fort Ellis research has encompassed multiple labs, projects, and many personnel, as it was a large collaboration looking at the effect of different farming systems on biodiversity at the macro (plant), mini (insect), and micro (-be) levels. Spanning multiple years, this project has been a massive undertaking that I briefly participated in but anticipate getting four publications out of (two more are in preparation).

Winter wheat

I previously presented this work at the 2017 Ecological Society of America (ESA) conference (poster: Ishaq et al ESA 2017 poster). And this field soil was the “soil probiotic” that was used in the follow-up greenhouse trial that I ran which was also published this year.

Soil bacterial communities of wheat vary across the growing season and among dryland farming systems.

Ishaq, S.L., Seipel, T., Yeoman, C.J., Menalled, F.D. 2020. Geoderma 358:113989.


Despite knowledge that management practices, seasonality, and plant phenology impact soil microbiota; farming system effects on soil microbiota are not often evaluated across the growing season.  We assessed the bacterial diversity in soil around wheat roots through the spring and summer of 2016 in winter wheat (Triticum aestivium L.) in Montana, USA, from three contrasting farming systems: a chemically-managed no-tillage system, and two USDA-certified organic systems in their fourth year, one including tillage and one where sheep grazing partially offsets tillage frequency. Bacterial richness (range 605 – 1174 OTUs) and evenness (range 0.80 – 0.92) peaked in early June and dropped by late July (range 92 – 1190, 0.62-0.92, respectively), but was not different by farming systems.  Organic tilled plots contained more putative nitrogen-fixing bacterial genera than the other two systems.  Bacterial community similarities were significantly altered by sampling date, minimum and maximum temperature at sampling, bacterial abundance at date of sampling, total weed richness, and coverage of Taraxacum officinale, Lamium ampleuxicaule, and Thlaspi arvense.  This study highlights that weed diversity, season, and farming management system all influence soil microbial communities. Local environmental conditions will strongly condition any practical applications aimed at improving soil diversity, especially in semi-arid regions where abiotic stress and seasonal variability in temperature and water availability drive primary production. Thus, it is critical to incorporate or address seasonality in soil sampling for microbial diversity.

A collaborative paper on zinc and rumen bacteria in sheep got published!

Zinc is an important mineral in your diet; it’s required by many of your enzymes and having too much or too little can cause health problems. We know quite a bit about how important zinc is to sheep, in particular for their growth, immune system, and fertility.  We also know that organically- versus inorganically-sourced zinc differs in its bio-availability, or how easy it is for cells to access and use it.  Surprisingly, we know nothing about how different zinc formulations might affect gut microbiota, despite the knowledge that microorganisms may also need zinc.

This collaborative study was led by Dr. Whit Stewart and his then-graduate student, Chad Page, while they were at Montana State University (they are now both at the University of Wyoming).   Chad’s work focused on how different sources of zinc affected sheep growth and performance (previously presented, publication forthcoming), and I put together this  companion paper examining the effects on rumen bacteria.

The pre-print is available now for Journal of Animal Science members, and the finished proof should be available soon. JAS is the main publication for the American Society of Animal Science, and one of the flagship journals in the field.

Zinc amino acid supplementation alters yearling ram rumen bacterial communities but zinc sulfate supplementation does not.

Ishaq, S.L., Page, C.M., Yeoman, C.J., Murphy, T.W., Van Emon, M.L., Stewart, W.C. 2018. Journal of Animal Science. Accepted. Article.


Despite the body of research into Zn for human and animal health and productivity, very little work has been done to discern whether this benefit is exerted solely on the host organism, or whether there is some effect of dietary Zn upon the gastrointestinal microbiota, particularly in ruminants. We hypothesized that 1) supplementation with Zn would alter the rumen bacterial community in yearling rams, but that 2) supplementation with either inorganically-sourced ZnSO4, or a chelated Zn amino acid complex, which was more bioavailable, would affect the rumen bacterial community differently. Sixteen purebred Targhee yearling rams were utilized in an 84 d completely-randomized design, and allocated to one of three pelleted dietary treatments: control diet without fortified Zn (~1 x NRC), a diet fortified with a Zn amino acid complex (~2 x NRC), and a diet fortified with ZnSO4 (~2 x NRC). Rumen bacterial community was assessed using Illumina MiSeq of the V4-V6 region of the 16S rRNA gene. One hundred and eleven OTUs were found with > 1% abundance across all samples. The genera PrevotellaSolobacteriumRuminococcusButyrivibrioOlsenellaAtopobium, and the candidate genus Saccharimonas were abundant in all samples. Total rumen bacterial evenness and diversity in rams were reduced by supplementation with a Zn-amino-acid complex, but not in rams supplemented with an equal concentration of ZnSO4, likely due to differences in bioavailability between organic and inorganically-sourced supplement formulations. A number of bacterial genera were altered by Zn supplementation, but only the phylum Tenericutes was significantly reduced by ZnSO4 supplementation, suggesting that either Zn supplementation formulation could be utilized without causing a high-level shift in the rumen bacterial community which could have negative consequences for digestion and animal health.

Featured Image Source: Wikimedia Commons

What I do for a living Part 1: DNA

Mr. DNA, Jurassic Park (1993)

Microbiome studies do not usually employ culturing techniques, and many microorganisms are too recalcitrant to grow in the laboratory. Instead, presumptive identification is made using gene sequence comparisons to known species. The ribosome is an organelle found in all living cells (they are ubiquitous), and it is responsible for translating RNA into amino acid chains.  The genes in DNA which encode the parts of the ribosome are great targets for identification-based sequencing.  In particular, the small subunit of the ribosome (SSU rRNA) provides a good platform for current molecular methods, although the gene itself does not provide any information about the phenotypic functionality of the organism.


Prokaryotes, such as bacteria and archaea, have a 16S rRNA gene which is approximately 1,600 nucleotide base pairs in length. Eukaryotes, such as protozoa, fungi, plants, animals, etc., have an 18S rRNA gene which is up to 2,300 base pairs in length, depending on the kingdom. In both cases, the 16 or 18 refers to sedimentation rates, and the S stands for Svedberg Units, all-together it is a relative measure of weight and size. Thus, the 18S is larger than the 16S, and would sink faster in water. In both genes, there exist regions which are conserved (identical or near-identical) across taxa, and nine variable regions (V1-V9) [1]. The variable regions are generally found on the exterior of the ribosome, where they are more exposed and prone to higher evolutionary rates.  Since the outside of the ribosome is not integral to maintaining its structure, the variable regions  are not under functional constraint and may evolve without destroying the ribosome. They provide a means for identification and classification through analysis [2-6]. The conserved areas are targets for primers, as a single primer can bind universally (to all or nearly-all) to its target taxa.  The conserved regions are all on the internal structure of the ribosome, and too much change in the sequence will cause its 3D (tertiary) structure to change, thus it won’t be able to interact with the many components in the cell.  Mutations or changes in the conserved regions often causes a non-functional ribosome and will kill the cell.


In addition to a small subunit, ribosomes also possess a large subunit (LSU rRNA), the 23S rRNA in prokaryotes, and the 28S rRNA in eukaryotes. Eukaryotes have an additional 5.8S subunit which is non-coding, and all small and large units of RNA have associated proteins which aid in structure and function. Taken together, this gives a combined 70S ribosome in prokaryotes, and a combined 80S ribosome rRNA in eukaryotes.

The ribosome assembles amino acids into protein chains based on the instructions of messenger RNA (mRNA) sequences.  (Image:

The way to study the rRNA gene is to sequence it.  First, you need to extract the DNA from cells, and then you need to make millions of copies of the gene you want using Polymerase Chain Reaction (PCR).  PCR and sequencing technology more or less work the same way as a cell would make copies of DNA for cell processes or division (mitosis). You take template DNA, building block nucleotides, and a polymerase enzyme which is responsible for reading the DNA sequence and making an identical copy, and with hours of troubleshooting get a billion copies!  Many sequencing machines use nucleotides that have colored dyes attached, and when a nucleotide is added, that dye gets cut (cleaved) off, and the camera can catch and interpret that action.  It then records each nucleotide being added to each separate DNA strand, and outputs the sequences for the microorganisms that were in your original sample!


The two main challenges facing high-throughput sequencing are in choosing a target for amplification, and being able to integrate the generated data into an increased understanding of the microbiome of the environment being studied. High-throughput sequencing can currently sequence thousands to millions of reads which are up to 600-1000 bases in length, depending on the platform. This has forced studies to choose which variable regions of the rRNA gene to amplify and sequence, and has opened up an arena for debate on which variable region to choose [2].  And of course, the DNA analysis of all this data you’ve now created is quickly being recognized as the most difficult part- which is what I focused on during my post-doc in the Yeoman Lab.  Stay tuned for a blog post on the wonderful world of bioinformatics!


  1. Neefs J-M, Van de Peer Y, Hendriks L, De Wachter R: Compilation of small ribosomal subunit RNA sequences. Nucleic Acids Res 1990, 18:2237–2318.
  2. Kim M, Morrison M, Yu Z: Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. J Microbiol Methods 2010, 84:81–87.
  3. Doud MS, Light M, Gonzalez G, Narasimhan G, Mathee K: Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients. Hum. Genomics 2010, 4:147–169.
  4. Yu Z, Morrison M: Comparisons of different hypervariable regions of rrs genes for use in fingerprinting of microbial communities by PCR-denaturing gradient gel electrophoresis. Appl Env Microbiol 2004, 70:4800–4806.
  5. Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR: Rapid determination of 16S ribosomal RNA sequences for phylogenetic analyses. Proc Natl Acad Sci USA 1985, 82:6955–6959.
  6. Yu Z, García-González R, Schanbacher FL, Morrison M: Evaluations of different hypervariable regions of archaeal 16S rRNA genes in profiling of methanogens by archaea-specific PCR and denaturing gradient gel electrophoresis. Appl Env Microbiol 2007, 74:889–893.