Mark Welch, J. Lab

Jessica Mark Welch
Associate Scientist

p: 508 289 7180
f: 508 457 4727

Image credit: Jessica Mark Welch et al., PNAS.1522149113

Using Spatial Structure to Understand Microbial Community Function

Bacteria play a critical role in both human health and the functioning of healthy ecosystems. In the human body, bacteria are necessary for normal development of the digestive and immune systems. Gut bacteria function as a digestive organ that provides energy and essential nutrients to the human body and produces a huge array of metabolic products. In the mouth, microbes colonize at high density on all available surfaces, including the teeth as well as the gums, tongue, and tonsils where bacteria interact directly with human tissues and the human immune system. Understanding the structure and function of these bacterial communities in the human body is critical to improving human health and developing personalized medicine.

In natural ecosystems, bacteria make up a large fraction of the total biomass, carrying out chemical transformations that influence, for example, the fate of carbon dioxide and nitrogen in the environment. Understanding these microbial ecosystems is critical to predicting and mitigating the outcomes of climate change. Microbes also play a key role in the physiology of keystone species on which the health of an ecosystem (e.g. a salt marsh) depends.

A key limitation in understanding microbial communities is the near-total absence of information on their micron-scale spatial structure. Microbes that are touching or located within a few micrometers of each other can acquire properties that one or both of them do not have independently, such as the ability to survive in an aerobic environment or invade a host cell and evade the host immune response. Therefore, to understand the properties of these microbes it is critical to know who their immediate neighbors are. Much information about complex microbial communities has been learned from DNA sequencing approaches, but the process of homogenizing the sample for DNA extraction destroys critically important spatial information.

My research program focuses on analyzing the spatial organization of microbial communities. My colleagues and I have developed a method that gives us the unique ability to simultaneously image and identify 15 or more microbial taxa, using a technique we call Combinatorial Labeling and Spectral Imaging – Fluorescence in situ Hybridization (CLASI-FISH). Using CLASI-FISH we are analyzing the spatial structure of bacteria in the human mouth, with the goal of understanding the normal structure and function of these communities in health and its disturbance in disease. We are also applying the method to studies of human gut bacteria transplanted into previously germ-free mice, as a simplified model system of the human gut microbiota.

An article by Ed Yong about our work on the spatial organization of the plaque microbiome is here.

The “hedgehog” consortium in dental plaque. Image credit: Jessica Mark Welch


Spatial Organization of the Oral Microbiome

The human oral microbiome consists of more than 700 bacterial species. In collaboration with Gary Borisy and Floyd Dewhirst of the Forsyth Institute, we are employing CLASI-FISH to investigate the spatial organization of the dental plaque biofilm as well as the microbiome on the tongue and other oral surfaces. In dental plaque we discovered an extraordinarily complex and highly organized microbial consortium, which we named a “hedgehog,” organized around filamentous corynebacteria. Within the structure, individual taxa are localized at the micron scale in ways suggestive of their functional niche in the consortium. The hedgehog consortium illustrates how complex structural organization can emerge from micron-scale interactions of the constituent organisms.

Biogeography of a human oral microbiome at the micron scale.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

Oligotyping Analysis of the Oral Microbiome: Turning Data into Information

To extract the maximum information from ribosomal RNA tag sequencing data, we are using an innovative, information-theory based approach called oligotyping developed by our colleague A. Murat Eren. Oligotyping, and the related Minimum Entropy Decomposition, allow us to partition sequencing data with single-nucleotide resolution. Using this method we are investigating the distribution patterns of species-level taxa in the oral microbiome. We discovered very closely related organisms with dramatically different distributions across oral sites, suggesting a level of ecological and functional biodiversity not previously recognized.

An article by Carl Zimmer about our work on oligotyping the oral microbiome is here.

The human oral microbiome, as analyzed by oligotyping. Image credit: A. Murat Eren

Oligotyping analysis of the human oral microbiome

Dynamics of tongue microbial communities with single-nucleotide resolution using oligotyping


Image credit: Jessica Mark Welch

Combinatorial Imaging of Gut Microbes in Gnotobiotic Mice

We are also investigating the microbes of the gut, using a mouse model. In collaboration with Jeffrey Gordon of Washington University, we are applying CLASI-FISH to germ-free mice that have been colonized with model microbial communities. By examining thin sections of small intestine, large intestine, and cecum, we are studying the distribution of 15 bacterial taxa as a first step in understanding the functional roles of these bacteria in mammalian digestion, metabolism, and immune system function.

Current Lab Members

Anthony McLean

Research Assistant I
p: 508 289 7293
f: 508 457 4727


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