Microbial populations in nature are faced with ever changing environmental conditions. One such fluctuation that cells need to perennially respond to is between different nutrients. While there is a rich body of work that has unravelled how microbes respond to chemically diverse nutrients, we do not have a good understanding of how cells react to changes in nutrient complexity. Unravelling these dynamics is necessary since natural environments are replete with polysaccharides such as cellulose, xylan, chitin and alginate. Microbes can metabolize polysaccharides to monosaccharides thereby changing nutrient complexity. Addressing these knowledge gaps and understanding the response of single cells to changes in nutrients were the core focal points of our study.
Studying cellular behaviours on ecologically relevant nutrients especially polysaccharides, however, is not as straightforward as other conventional nutrients like glucose. Thus, we were faced with multiple questions. What organism should we use? Which polysaccharide is experimentally amenable to approaches like microfluidics, which allow single cell growth measurements? How do we quantitatively analyse growth properties, mobility and behavioural differences of individual cells? The solution to these questions was to tap into established research, repurpose algorithms and collaborate to build new analyses.
1. The study organism: It was a conscious decision to choose Caulobacter crescentus CB15. First, it has been heavily studied with respect to cell biology but there has been very little ecology focussed work with the bacterium. Second, there are several polysaccharide degrading enzymes encoded in the genome. Thus, the wealth of pre-existing knowledge as well as little ecological understanding represented a great opportunity to understand cellular dynamics in nature-like conditions.
2. The polysaccharide: We chose xylan, a polysaccharide predominantly consisting of repeating monomeric units of xylose. Xylan is one of most prevalent polysaccharides in natural ecosystems along with cellulose, and chitin and C. crescentus has several xylanases. For instance, 10-30% of wood biomass can consist of xylan. Importantly, relatively pure xylan can be bought commercially (basically powdered birchwood) and is soluble in water over physiologically relevant concentrations (0.1-2%), xylan. This allowed us to study behaviours of single cells within microfluidic devices in response to resources of distinct complexities: polysaccharide xylan and its corresponding monomer xylose.
3. Analytical tools: Here we tapped into multiple tools already published in the field. superSegger is an amazing imaging analysis pipeline that works great directly out of the box and ilastik is continuing to be a great ever-developing tool for cell segmentation. We combined these tools with new scripts that enabled us to build lineage trees of cellular groups, perform quantitative growth analysis of single cells and quantify dispersal or aggregation dynamics of individuals in populations.
Caulobacter crescentus cells growing on xylan form colonies. In the video, cells that arise from the same progenitor are coded with the same unique colour.
Finally, we blended all these approaches to study the growth and behavioural dynamics of C.crescentus cells on xylan or xylose. We found that cells are not locked in one behavioural state. Rather they tune their behaviours based on the presence of xylan or xylose. Cells form colonies in the presence of the polysaccharide xylan so that they can optimally benefit from each others degradative activities. When simpler nutrients like xylose become available, cells within colonies disperse. This is because the benefit of colony formation disappears in the presence of monosaccharides and solitary behaviours can serve to reduce intercellular competition.
So essentially the learning for humans from their tiny microbial counterparts is: When environmental complexity increases it helps to team-up and benefit from each other's activities!
Read more in our paper in ISME J.
Check out a twitter thread, where I summarise the key findings