Please go to the College of Arts & Sciences page for a lay summary of our work.
We are interested in biomass accrual – how cells, traits, individuals, populations, and ecosystems gain energy and materials – and why it varies. Accurate prediction of biomass accrual lies at the foundation of both basic and applied biology. Such a predictive understanding is needed to not only solve emerging environmental issues, but also aid in the long-standing theoretical pursuit for a synthetic (cross-scale) understanding of biology.
To understand change in biomass, it helps to know what makes up biomass. This Voronoi tree diagram of the composition of a growing E. coli cell provides a general picture (Milo & Phillips 2015). Viewing this plot from a biogeochemical perspective, the common stoichiometry of protoplasmic life, and fundamental anabolic processes such as protein synthesis become readily apparent (e.g., see figure below about the proportion of nitrogen and phosphorus in various biomolecules; Sterner & Elser 2002).
Consequently, we know much about the relationship between growth and bulk elements (e.g., N, P) because they are required for ribosome biogenesis and protein synthesis. Agricultural demand for these elements has altered the cycles of these elements, impacting the functioning of non-target ecosystems and the ecology and evolution of biota in the Anthropocene. As such, sustainable management of biogeochemical cycles requires a fundamental understanding of biomass accrual. However, precise prediction of biomass accrual eludes us, largely because of diversity in nutrient-growth functions among genotypes, species, and ecosystems.
Monod (1949) delves into his landmark review highlighting the need for formal models describing growth, enterprises that “have repeatedly proved sterile”. Seventy years on, there have been few efforts as fertile as Monod’s. Nevertheless, the performance of the model equating growth to nutrient supply varies considerably in natural conditions and is rather futile in describing growth at higher levels of organization (e.g., productivity of ecosystems). Droop (1973) discovered the role of nutrient quotas in growth that has performed better in field conditions, and in describing ecosystem productivity, although there is considerable variation in fit (Sommer 1991).
We contend that the Law of Minimum (Sprengel 1838; Leibig 1855), on which aforementioned models are based upon, rarely holds. This is not surprising given genomic-era data on the system-wide adjustments organisms make in response to changes in supply of elements that are required for protein assembly (in the presence of enough energy, of course). Such responses should alter the quotas of multiple other elements, possibly with huge growth implications. As such, we measure the entire suite of elements involved in the system to discover dynamics in quotas of the 20-odd biogenic elements as a function of growth and production. We believe that such information illuminates the entire suite of mechanisms underlying growth dynamics as energy, nitrogen, and phosphorus supplies change (reflecting global change scenarios).
Jeyasingh et al. (2020).
As a word of reassurance to the chemistry-weary biologists, we do not do much organic or biochemistry. We do bio-inorganic chemistry, inspired by the pioneering work of renowned chemist RJP Williams (e.g., Williams & da Silva 2006; Williams & Rickaby 2012). We use simple rules of the Periodic Table, and basic physicochemical principles (e.g., mass balance) to dig into the foundations of biology. For example, we consider any biological system (e.g., cell, tissue, organism, population, community, ecosystem) as a collection of elements. These elements enter the system, perform key functions (including growth), and leave the system. Chemical properties have a huge bearing on these fluxes, and measuring an element in one pool enables predictions about others (Jeyasingh et al. 2014). Quantifying the fluxes of multiple elements simultaneously is challenging, but it is quite fun and rewarding!
What have we learnt? Even in experimentally enforced single nutrient limitation, biomass production is constrained by imbalances in multiple other elements (Jeyasingh et al. 2020; Ipek & Jeyasingh 2021). Moreover, populations adapt to mitigate such imbalances (Jeyasingh et al. in review). Such system-wide elemental imbalances are consistent with those of other systems biology observations. For example, Daphnia in low phosphorus environments differentially express about 30% of the genes in their genome (Jeyasingh et al. 2011) which code for a variety of proteins performing a variety of functions, each with its unique elemental stoichiometry (notably in catalytic metals). How do other elements (i.e. those not directly involved in peptide synthesis and assembly) impact growth? A look at the ATP budget of a growing cell is informative. While peptide anabolism is the largest sink (~4 ATP per peptide bond) ionic balance is the 2nd largest (Milo & Phillips 2015). Indeed, minimizing ATP allocation to ionic balance machinery has a large effect on the efficiency at which elements involved in protein anabolism (i.e. nitrogen, phosphorus) are converted into biomass.
Jeyasingh et al. (unpublished data)
Scaling these systems-biological observations to ecosystems will have much to contribute toward predicting nutrient-productivity relationships. For example, phosphorus explains less than half of the variation in chlorophyll among lakes (Quinlan et al. 2021). Given the common mechanism by which proteins are made (Loladze & Elser 2011; Kafri et al. 2016), this weak relationship is somewhat puzzling. Our recent multi-elemental observations on lakes indicate staggering variation in the supplies of multiple elements among lakes. For example, Lind et al. (2021) found three orders of magnitude variation in total iron among Oklahoma lakes, while Jeyasingh et al. (in prep) found that despite similar supplies of N & P, lakes vary strikingly in several other elements, and occupy unique positions in multi-elemental space. We are only starting to make sense of such variation and its relevance to the structure and functioning of ecosystems (see Kaspari 2021 for a treatise).
We employ theory, lab experiments, field surveys, and metadata to improve our understanding of the fundamental links among energy/material supply and the quantity and quality of biomass accrued at different levels of organization (cells, organs, individuals, populations, ecosystems). We are set up to study freshwater taxa and ecosystems, although we continue to work collaboratively in a variety of systems. Positions for undergraduate, graduate, and postdoctoral research are available or can be developed. Email Puni (puni.jeyasingh@okstate.edu).
Droop M (1973) Some thoughts on nutrient limitation in algae. J Phycol 9:264–272.
Kafri M et al. (2016) The cost of protein production. Cell Reports 14: 22-31.
Kaspari (2021) The Invisible Hand of the Periodic Table: How Micronutrients Shape Ecology. Ann Rev Ecol Evol Syst.
Liebig J (1855) Principles of agricultural chemistry. Dowden, Hutchinson & Ross, London.
Loladze I, Elser JJ (2011) The origins of the Redfield nitrogen-to-phosphorus ratio are in a homoeostatic protein-to-rRNA ratio. Ecol Lett 14: 244-250.
Milo R, Phillips R (2015) Cell Biology by the Numbers. Garland Science.
Monod J (1949) The growth of bacterial cultures. Annu Rev Microbiol 3:371–394.
Quinlan R et al. (2021) Relationships of total phosphorus and chlorophyll in lakes worldwide. Limnol Ocenogr 66: 392-404.
Sommer U (1991) A comparison of the Droop and the Monod models of nutrient limited growth applied to natural populations of phytoplankton. Func Ecol 5: 535-544.
Sprengel C (1838) The science of cultivation and soil amelioration. Immanuel Muller Co., Leipzig, Germany.
Sterner RW, Elser JJ (2002) Ecological Stoichiometry. Princeton University Press.
Williams RJP, Rickaby REM (2012) Evolution’s Destiny. RSC Publishing.
Williams RJP, da Silva JJ (2006) The chemistry of evolution. Elsevier Science.
Please see Publications for papers from our group.