In a post yesterday and another today, we’re considering the incredibly sophisticated decision-making process that determines whether the bacterium Bacillus subtilis (pictured above) will crowdsource exogenous DNA and integrate it into its own chromosome. By “crowdsource” I mean take up similar genetic material from its environment and integrate that xenogenic DNA into its own genome.
Bacteria perform computation for decisions in transcription factor networks. They also use hierarchical layers of the sensory network to break problems down into smaller pieces or generalize classes of problems. Previously I covered some of the early steps towards the state of competence, which includes a special attachment to RNA polymerase called Sigma-H that changes which set of genes are targeted as well as four proteins that control the ComK promoter.
Let’s look now at post-transcriptional and protein level control of ComK. As I mentioned yesterday, ComK is the master transcriptional regulator of the competence genes.
Late Acting Controls
In transcription networks, the interaction between the physiological signals and their transcription factors happens extremely fast (subsec timescales). The time it takes for altered transcription factors to modulate DNA expression is also very fast (second timescale), but then things slow down. Transcription and translation occur on a timescale of minutes, and protein production can take up to an hour (Alon 2019). Since the time it takes transcription factors to modulate DNA expression is fast this is typically where regulation occurs as it allows for agility and efficiency.
However, in addition to the transcriptional layer of regulation, there is also control over ComK mRNA (degradation via Kre) (Gamba et al. 2015) and control of the protein level itself (proteolysis via the ClpCP proteases). Small variations in ComK levels strongly affect the probability of competence as an outcome. This means that both of these are later acting controls that have the ability to modulate ComK based on the developing environmental situation. This provides additional opportunities for the cell to adjust ComK accumulation and prevent an inappropriate decision to crowdsource exogenous DNA. We might expect this in a scenario where a bacterium moved towards competence, but then changed course due to new information.
Intelligent Design Makes a Prediction for “Crowdsourcing”
Having reviewed some of the known regulatory mechanisms controlling crowdsourcing (natural competence) in Bacillus subtilis, we can now consider a key prediction that flows from an intelligent design perspective.
In human-engineered complex information-processing systems, the integration of externally sourced code or components is a high-risk activity. It is typically performed only, when necessary, with careful coordination, modularity, and compatibility checks. Applying this same logic to biological systems, an ID framework predicts that the cell would not initiate DNA uptake (crowdsourcing) indiscriminately.
Instead, the cell is expected to compute the likely benefit of genetic exchange before committing to competence. Specifically, B. subtilis would likely require at least two critical evaluations:
- Does the cell actually need external DNA? It would assess whether its current internal genetic resources are insufficient to meet present or anticipated environmental challenges. Stress signals themselves may serve as a proxy for this internal deficiency.
- Is useful genetic information available in the local population (“the crowd”)? The cell would need some mechanism to gauge whether beneficial DNA is likely present in its immediate environment before investing in the costly process of becoming competent.
Next, I’ll share some preliminary data — that appears to be a strong candidate for #2.
Quorum Sensing’s Role In “Crowdsourcing”
Quorum sensing is the process that bacteria use to communicate with each other via chemical signals. There are two quorum-sensing factors, ComX and CSF (competence stimulating factor) that play a role in B. subtilis crowdsourcing (Maier 2020).
ComX is a quorum signal whose extracellular concentration reflects the density of neighboring B. subtilis cells producing the pheromone (Yajima 2014). When there are sufficient bacteria around, ComX binds to a membrane-embedded histidine kinase and initiates a phosphorylation cascade which triggers production of another protein ComS. ComS then promotes DNA crowdsourcing. This system enables individual bacteria to evaluate whether the community size is adequate for DNA crowdsourcing.
CSF is a quorum-sensing peptide produced from the phrC gene. Like other Phr peptides, CSF is synthesized as a variable length peptide that is secreted. This is then processed extracellularly, producing short mature peptides (typically five amino acids) that are then transported back into the cell through the Opp oligopeptide transporter (Perego 2013). Once inside the cell, CSF inhibits the RapC regulatory protein promoting ComS production.
It is not known what the Phr peptides are sensing or communicating back to B. subtilis. Since these are excreted and can be pumped back into the cell, it seems likely that they would be prime candidates for bringing information about extracellular DNA concentration, sequence, and usefulness. I offer the caveat that this is strictly a hypothesis. It has no experimental evidence at present that I’m aware of, as I could find little to nothing in the literature about it. Current thought is that Phr peptides are primarily signals of population state rather than direct sensors of available or useful DNA.
Key experiments to refute or justify this hypothesis might involve looking at whether the extracellular processing steps are regulated by the type or amount of DNA that is around. This might involve looking to see if there are DNA binding properties on the proteases that process these peptides.
How Design Thinking Can Help Us Do Better Biology
The competence system of B. subtilis provides a striking example of sophisticated biological information processing. Before a bacterium commits to taking up and integrating external DNA, it must integrate multiple layers of information, including nutrient status, population signals, developmental state, and regulatory feedback. From a design perspective, one aspect that stands out is the architecture of this decision-making system. The competence network is deeply integrated with other cellular programs, such as the sporulation pathway, while also displaying a highly organized structure of signal integration, regulation, and control. Rather than appearing as a collection of haphazard connected components, the system functions as a coordinated network with clearly defined regulatory roles.
What would it mean to take a design approach to understanding this biological system? Minimally it would mean assuming good design. But I would argue that the best way to approach the system is the reverse engineering approach: thinking about system requirements necessary to build such a sophisticated signaling system, building a system model based on existing literature, and then making assumptions of optimal design as one considers hypotheses to test.
Whether one approaches biology from an evolutionary or a design perspective does influence the questions that are asked and the types of explanations that are considered. The biological observations themselves should remain grounded in experimental evidence. However, the conceptual framework used to interpret those observations can shape which hypotheses are prioritized and which experiments are pursued. In this sense, philosophy and biology inform one another rather than existing as separate realms of inquiry.
Some still argue that evolutionary processes can ultimately produce highly optimized biological systems such as the B. subtilis competence system. Certainly, as a theory, evolution did not historically predict this, and Darwin had no idea that such sophistication existed. I have yet to be convinced experimentally or philosophically that random mutation and natural selection can account for something like this gene regulatory network.
If you aren’t sure about the design approach, give it a try. To adapt the words of Theodosius Dobzhansky, I’m persuaded that nothing in biology makes sense except in light of intelligent design.
References
- Alon, Uri. An introduction to systems biology: design principles of biological circuits. Chapman and Hall/CRC, 2019.
- Brinsmade, Shaun R. 2017. “CodY, a Master Integrator of Metabolism and Virulence in Gram-Positive Bacteria.” Current Genetics 63 (3): 417–25.
- Britton, Robert A., Patrick Eichenberger, Jose Eduardo Gonzalez-Pastor, et al. 2002. “Genome-Wide Analysis of the Stationary-Phase Sigma Factor (Sigma-H) Regulon of Bacillus Subtilis.” Journal of Bacteriology 184 (17): 4881–90.
- Chumsakul, Onuma, Hiroki Takahashi, Taku Oshima, et al. 2011. “Genome-Wide Binding Profiles of the Bacillus Subtilis Transition State Regulator AbrB and Its Homolog Abh Reveals Their Interactive Role in Transcriptional Regulation.” In Nucleic Acids Research, vol. 39. no. 2. Preprint. https://doi.org/10.1093/nar/gkq780.
- Gamba, Pamela, Martijs J. Jonker, and Leendert W. Hamoen. 2015. “A Novel Feedback Loop That Controls Bimodal Expression of Genetic Competence.” PLoS Genetics 11 (6): e1005047.
- Maier, Berenike. 2020. “Competence and Transformation in Bacillus Subtilis.” Current Issues in Molecular Biology 37 (January): 57–76.
- Paget, Mark S. 2015. “Bacterial Sigma Factors and Anti-Sigma Factors: Structure, Function and Distribution.” Biomolecules 5 (3): 1245–65.
- Perego, Marta. 2013. “Forty Years in the Making: Understanding the Molecular Mechanism of Peptide Regulation in Bacterial Development.” PLOS Biology 11 (3): e1001516.
- Serrano, Ester, Rubén Torres, and Juan C. Alonso. 2021. “Nucleoid-Associated Rok Differentially Affects Chromosomal Transformation on Bacillus Subtilis Recombination-Deficient Cells.” Environmental Microbiology 23 (6): 3318–31.
- Verhamme, Daniël T., Taryn B. Kiley, and Nicola R. Stanley-Wall. 2007. “DegU Co-Ordinates Multicellular Behaviour Exhibited by Bacillus Subtilis.” Molecular Microbiology 65 (2): 554–68.
- Yajima, Arata. 2014. “Recent Progress in the Chemistry and Chemical Biology of Microbial Signaling Molecules: Quorum-Sensing Pheromones and Microbial Hormones.” Tetrahedron Letters 55 (17): 2773–80.