Executive Summary

Aquarius investigates differences in engineered chassis behavior in laboratory conditions versus simulated real-world aquatic environments. Through three case studies, we clarify critical differences in survival, gene expression, and functional performance of chassis under controlled laboratory and simulated natural conditions.

I. Marine Corrosion Prevention with Bacillus subtilis

Engineered B. subtilis strains showed enhanced biofilm traits in lab media but failed to form robust biofilms or prevent corrosion in simulated seawater environments. Natural strain 3610 outperformed engineered variants. RNA-seq and 16S analyses revealed environmental stress and microbial competition significantly impacted gene expression and chassis persistence.

II. Freshwater Harmful Algal Bloom (HAB) Remediation with Cyanophage and Acinetobacter baylyi

A. baylyi persisted in static laboratory cocultures but was outcompeted by microbial competitors in flowing lakewater microcosms. Under microcosm conditions, 16S amplicon sequencing and colony counts indicated a reduction in A. baylyi survival that corresponded with an increase in the relative abundance of competitor species. Preliminary RNA sequencing results identified differentially expressed genes that indicate differences in A. baylyi functioning across the two conditions.

III. Biofilm Removal in Household Pipes Using Phage Therapy

Phages lysed mycobacteria effectively in lab assays but degraded quickly and failed to persist or reduce biofilms in PVC pipe microcosms. Microscopy and 16S sequencing revealed complex biofilm communities and limited phage impact. We are analyzing novel RNA-seq data to identify biofilm-associated gene expression that may inhibit phage efficacy.

Bioinformatics & RNA-Seq Meta-Analysis

We conducted a meta-analysis of transcriptomic and metatranscriptomic data to identify genes and pathways differentially expressed between lab and environmental conditions. These insights are guiding our development of design principles for synthetic biology in aquatic systems.

Aquatic Case Study I:

**Corrosion Prevention Using Engineered Bacillus subtilis in Marine Environments**

Overarching Goal: To compare ability of engineered B. subtilis to prevent corrosion in lab conditions versus simulated real-world marine seawater conditions.

Experiment 1:

**Construction of Engineered B. subtilis Strains**

Data Analysis/Interpretation:

We conducted colony PCR for the constructed plasmid L0 SapI-J04450-TapA-SipW-TasA, only 2 out of 24 PCR reactions yielded a band of the expected length, suggesting that the SapI insert has a low ligation efficiency, possibly due to its short three-base-pair fusion sites, resulting in a high possibility of mismatch.

The integration vector pBS1C-N was designed to integrate into the AmyE locus in the Bacillus subtilis genome. Upon successful transformation, the vector disrupts the native amylase gene, thereby stopping the strain’s ability to hydrolyze starch. This disruption enables a straightforward functional screening method: colonies with successful genomic integration will fail to degrade starch and appear dark blue when stained with iodine solution, whereas wild-type colonies will be orange due to starch breakdown. Transformation into B. subtilis 168 yielded colonies for all four constructs showed dark blue in iodine staining, confirming the loss of starch degradation, showing that the vectors were successfully integrated into B. subtilis 168 genome. When labeling Petri dishes, the B. subtilis 168 tapA–sipW–tasA+ strain was abbreviated as TST for convenience.

Experiment 2:

**Establishing growth curves to compare growth dynamics of B. subtilis 168, 3610, and the 4 engineered 168 variants under laboratory conditions**

Data Analysis/Interpretation:

Both the 24- and 36-hour growth curves indicated that the concentration of the xylose inducer had no significant effect on bacterial growth in standard LB medium, which does not promote biofilm formation. The dark blue line shows that the absence of xylose resulted in no major difference compared to other concentrations. The four engineered strains and the unmodified laboratory strain Bacillus subtilis 168 exhibited similar growth rates, whereas the natural strain B. subtilis 3610 grew substantially faster. Additionally, after the experiment, visible cell clusters were observed in several wells containing B. subtilis SinI+ and B. subtilis BslA+ strains, which may explain the pronounced fluctuations in OD readings toward the end of the growth curve.

Experiment 3:

**Evaluating the motility of B. subtilis 168, 3610, and the 4 engineered 168 variants**

Data Analysis/Interpretation:

Only Bacillus subtilis 3610 exhibited both swarming and sliding motility, confirming that it remains the only strain possessing both EPS-driven sliding and flagellum-driven spreading. None of the engineered modifications produced sufficient EPS to support sliding motility. Among the engineered strains, B. subtilis 168 and its SinI+ variant spread across the entire Petri plate, demonstrating strong flagellum-dependent swarming. The B. subtilis 168 BslA+ and TapA–SipW–TasA+ variants covered approximately 67% of the plate surface, showing moderate swarming. In contrast, the B. subtilis 168 TasA variant displayed neither swarming nor sliding, possibly due to cellular toxicity associated with TasA overexpression.

Experiment 4:

Determining effect of our genetic modifications on biofilm robustness and structure through characterization of biofilm and colony morphology of laboratory and engineered strains of Bacillus subtilis

Data Analysis/Interpretation:

Bacillus subtilis 3610 formed a distinct, slightly brown biofilm, while only the SinI+ variant exhibited biofilm-like folds and wavy colony margins. All other engineered strains produced smooth, flat colonies lacking biofilm characteristics.

When comparing media, LB medium did not support biofilm development and is therefore suitable for general culture rather than biofilm assays. In contrast, both SinI+ and B. subtilis 3610 formed biofilm structures on MSgg medium.

Regarding inducer application, sprinkled xylose on MSgg agar surface resulted in uneven colony morphology, likely due to heterogeneous inducer distribution across the surface. In contrast, adding xylose into the MSgg medium resulted in structured colonies. Adding 0.03% or 0.2% xylose produced no significant change in biofilm development, indicating that these concentrations were insufficient to elicit measurable promoter activation difference or alter biofilm formation dynamics.

Experiment 5:

Evaluating corrosion protection abilities of each strain on steel surfaces in a simulated marine environment

Data Analysis/Interpretation:

Visually, the seawater control group, which was not inoculated with B. subtilis, exhibited a thick oxidation layer on the steel surface, while moderate oxidation was observed in the B. subtilis 168 treated samples. Oxidation on the remaining samples was minimal and much less apparent. Scanning electron microscopy (SEM) further revealed extensive corrosion on both the three-day and seven-day control plates. Dennis Manos, the CSX Professor of Applied Science in William and Mary, interpreted the structures as oxidation structures along with tetrahedral crystal habit of magnetites and needle-like lepidocrocite structures. In contrast, the three-day B. subtilis 168 sample displayed distinct corrosion lines interspersed with deposits of irregularly shaped compounds—patterns similar to nano-structured calcium silicate(Johnston et al., 2008). Similar surface features were also present in the three-day B. subtilis 3610 sample and showed up in a region of the seven-day SinI+ plate. Notably, in other regions of the three-day B. subtilis 3610 plate, as well as on the three-day and seven-day BslA+ and SinI+ samples, we observed a novel surface structure: parallel, unidirectional apparently inorganic crystals forming across the steel in an anisotropic morphology that appears to follow the underlying substrate grains. Our phone and SEM pictures suggested the Bacillus subtilis in the microcosms noticeably altered the corrosion behavior and protected against corrosion. These formations differ markedly from previously published SEM images of B. subtilis–related corrosion (Guo et al., 2017; Wang et al., 2020), which were obtained under sterile laboratory conditions. In contrast, our study employed non-sterile microcosms designed to mimic natural marine environments, which showcased that these unique crystalline structures may arise from species interactions in aqueous environments.

Experiment 6:

Analysis of gene expression differences between lab and microcosm environments in strains with strong corrosion protection

Data Analysis/Interpretation:

16S sequencing revealed substantial colonization by non-Bacillus subtilis species across all seawater microcosm samples, indicating that mixed microbial communities developed under non-sterile conditions. Among the three tested strains: wild-type B. subtilis 3610, SinI+, and BslA+, the wild-type strain showed minimal persistence within these communities, whereas both engineered strains displayed moderate survival. Community composition varied strongly with inoculum concentration. In microcosms inoculated with 25% bacterial culture, Ochrobactrum dominated the population and emerged as the most abundant non-Bacillus genus. In contrast, microcosms inoculated with only 0.5% bacterial culture were consistently enriched in Acinetobacter. These results suggest that inoculum concentration not only shapes community composition but may also influence competitive interactions among resident taxa, providing a potential ecological explanation for the observed differences in corrosion-protection outcomes described in Experiment 4.

RNA sequencing results revealed that sporulation-related genes were downregulated in all three Bacillus subtilis strains under marine microcosm conditions. In contrast, metabolic genes were upregulated across all strains, with the SinI+ and BslA+ variants showing increased expression of genes involved in ATP binding, rRNA binding, and translation. Notably, the BslA+ strain exhibited specific upregulation of genes associated with flagellar assembly, suggesting an enhanced motility response to the seawater environment. The RNA sequence strongly supports that strains were behaving differentially in simulated natural environments and lab environments.

Aquatic Case Study II:

Freshwater Algal Bloom Remediation

Overarching Goal: To compare behavior and ability of cyanophages and/or Acinetobacter baylyi to remediate HABs in lab conditions versus simulated real-world conditions.

Experiment 7:

Microcystis Cyanophage Isolation for Harmful Algal Bloom Remediation

Experimental Goal:

To isolate (and potentially engineer) novel Microcystis cyanophages for harmful algal bloom (HAB) remediation as a case study to compare phage behavior in laboratory conditions versus simulated real-world environments.

Data Analysis:

Plaque formation on a Microcystis lawn is a strong indicator of phage presence, however we were unable to consistently propagate any putative cyanophage.

Interpretation:

Our results highlight a need for SynBio solutions that consider the ecological complexities of real-world water systems in which they must ultimately be deployed. Our attempts to isolate and engineer cyanophage offer a case-study in the effects of real-world chassis behavior and community dynamics on the effectiveness of SynBio-based aquatic remediation solutions.

Importantly, our results indicate that M. aeruginosa may have strong anti-phage defense systems that complicate phage isolation and could limit the feasibility of phage-based HAB treatments in the field. We have identified two major limitations of cyanophage isolation and cyanophage-based HAB treatment:

First, M. aeruginosa may rapidly evolve phage resistance. About 7% of M. aeruginosa’s genome is composed of transposases that can rearrange the species’ abundant mobile genetic elements (Frangeul et al., 2008) and drive evolution in the field and in the lab (Stark et al., 2024). Constant re-shuffling of the genome can rapidly generate novel phage-resistant genotypes—and our discussion with IHP experts indicated that resistance evolution can occur even at the level of a single culture. Rapid host resistance evolution at the culture level may prevent continual propagation of newly-isolated phages in the lab, and analogous evolution at the HAB population level would likely limit in vivo deployment.

Second, M. aeruginosa phages may exhibit high rates of lysogeny (integration and latency within the host genome), particularly during HAB formation (Huang et al., 2025). Lysogeny could limit novel cyanophage isolation, as there may be few free-floating phage available to isolate. Interestingly, the turbidity of our plaques may indicate a level of lysogeny, which could explain the putative cyanophage’s inconsistent propagation. Lysogeny often provides host cells with immunity to other infecting phages (Buchner et al., 2024), and lysogeny’s prevalence in HABs could limit cyanophage treatment viability in vivo by preventing reinfection.

Experiment 8:

**Comparison of Acinetobacter baylyi Behavior in Laboratory vs Simulated Real-World Microcosms**

Overall Experimental Goal:To test habitat remediation with Acinetobacter baylyi ADP1-ISx as a case study comparing bacterial behavior (persistence and gene expression) in laboratory conditions versus simulated real-world environments in order to inform the development of design principles for synthetic biology applications in aquatic systems.

Experiment 8a:

**Estimating A. baylyi survival in microcosms and control cocultures via colony counts**

Data Analysis:

Control coculture spread plates consistently formed A. baylyi lawns throughout the time course, while microcosm spread plates yielded decreasing A. baylyi colony counts over the span of the experiment.

Interpretation:

The reduction in microcosm A. baylyi colony formation over time (and as compared with the control) suggests that the microcosm conditions adversely affected A. baylyi survival over the course of the experiment.

Experiment 8b:

Quantifying species abundance in microcosms and control cocultures via 16S amplicon sequencing

Data Analysis:

The average microcosm A. baylyi population declined from an initial 73.58% abundance (on day 1) to 7.83% abundance (day 7). Control abundances on day 7 were approximately comparable to those measured on day 1 (at 77.41% on day 7 as compared to 81.33% on day 1).

Figure: Mean A. baylyi Relative Abundance in Cocultures and Microcosms vs Days Post-Inoculation. Error bars display 95% confidence intervals for each mean.

Interpretation:

The substantial reduction in microcosm A. baylyi relative abundance over the course of the experiment (and as compared to the control) suggests that A. baylyi was outcompeted by native lakewater organisms within a week after initial microcosm inoculation.

Figure: A sample of native Lake Matoaka organisms, including various diatoms, cyanobacteria, and green algae under a standard light microscope. Our 16S results suggest that native microbes outcompeted A. baylyi in lakewater microcosms.

Experiment 8c:

Quantifying differential gene expression of A. baylyi in microcosms and control cocultures via RNA sequencing

Data Analysis:

After 24 hours, the most highly upregulated genes in A. baylyi microcosms as compared to control cocultures (indicated by high log2 fold change values) included genes encoding an NAD(P)/FAD-dependent oxidoreductase, an ATP-dependent Clp protease ATP-binding subunit, a mechanosensitive ion channel, and a PA1571 family protein. A. baylyi genes significantly downregulated in the microcosms included genes encoding LyrR family transcriptional regulators, a MATE family efflux transporter, and the epoxyqueuosine reductase QueH.

Interpretation:

Preliminary evidence of differential gene expression after 24 hours suggests that specific aspects of A. baylyi’s behavior and functioning are concretely affected by real world conditions and that A. baylyi likely does not function as effectively in a real world environment as it does in traditional in vitro cocultures. We are currently in the process of analyzing and interpreting RNAseq data to quantify A. baylyi differential gene expression between microcosms and control cocultures at all three timepoints.

Overall Interpretation:

Our results illustrate that engineered chassis may not persist and function as effectively in real-world environments compared with the lab settings in which they are typically tested. Synthetic biologists should test their constructs in simulated real-world environments in order to identify and address limitations associated with the effects of in vivo conditions prior to deployment.

We conclude that Acinetobacter baylyi’s survival and functioning may be limited in a real lakewater environment, despite effective persistence in cocultures. We observed a substantial decline in A. baylyi relative abundance (according to 16S sequence data) under simulated lakewater conditions, indicating that A. baylyi was outcompeted by native lake species. Colony counts further suggest that A. baylyi’s population declined over the course of the microcosm experiment, suggesting that lakewater conditions adversely affected survival.

Aquatic Case Study III:

Removal of Biofilms in Household Pipes

Overarching Goal: To compare ability of phages to lyse biofilms in lab conditions versus real world conditions of household pipes

Experiment 9:

Determining efficiency of specific mycobacteriophages to lyse mycobacteria under laboratory conditions

Data Analysis/Interpretation:

Phage titers ranged from approximately 10^10 to 10^13 PFU per milliliter of lysate. Phage CrimD and Phage Neighly formed webbed lysis at 10^10 dilutions and Phage Raid at 10^8 dilutions, successfully killing most of the mycobacterial lawn. This illustrated the ability of phage to kill mycobacteria even at high dilutions.

Experiment 10a:

Determining titer of viable bacteria in the microcosm effluent before and after phage infection

Data Analysis:

There was not a significant difference in the bacterial titer before and after phage infection (p-value = 0.604), which was determined using a Welch t-test.

Interpretation:

Phage treatment did not have a significant effect on bacterial titer in the effluent, suggesting that one treatment of phage was not significant in decreasing bacterial population in the biofilm.

Experiment 10b:

Determining phage survivability in microcosm conditions

Raw Data:

Initial phage titer inoculated uniformly throughout the microcosms: 4.5*10^12

Figure: Phage titer from effluent after 24 hours.

Data Analysis/Interpretation:

Phage titer decreases substantially after 24 hours in microcosm effluent, likely due to the proteases and other degradation factors that are inherent to realistic and dynamic environments.

Experiment 10c:

Testing phage presence in microcosm effluent at the final time point

Raw Data:

There were no visible plaques in the plaque assays from the final effluent.

Data Analysis/Interpretation:

The lack of phage presence in the effluent at the final time point signifies that phage did not adhere strongly enough to the biofilm or phage no longer were able to sustain themselves in the biofilm. This may be because of the decrease in bacterial population or the structure of the biofilm preventing the phage from surviving for long periods of time.

Experiment 10d:

Determining the structure of the biofilm in the pipe following phage treatment

Data Analysis:

Figure: Average color distributions on biofilm surfaces with phage and without phage treatment.

Interpretation:

The PVC pipes that were treated with phage had what resembled plaque-like holes in biofilm formation, with less surface area covered by biofilm compared to the biofilm that was flushed with standard tap water with no phage added. There were also less visible red bacteria, signifying that the RFP-transformed mycobacteria was less present after phage treatment.

The colors represent the distribution of height throughout the biofilm. Since we saw no significant differences in maximum and minimum heights, we chose to focus on the height distribution based on the pseudocolors that were assigned by the HIROX microscope program. Blue represents the lowest height range, green being the second lowest, yellow being greater, and red being the highest height range.

There is a trend (p-value = 0.067) of lower range colors being predominant in the pipes treated with phage, meaning that although the range of biofilm height remains relatively consistent, the height distribution is skewed towards the lower end after phage treatment. The lack of disparity in maximum height is consistent with literature that suggests that phage clusters in regions upon infection of the biofilm, and the extracellular matrix itself is not heavily affected by phage treatment (Testa, 2019).

Experiment 10f:

Determining bacterial community structure of microcosm biofilm

Raw Data:

Table: Outputs from running the 16s sequence through Kraken2 and Bracken with species and abundances.

Data Analysis:

The 16s sequencing results suggest that the biofilm largely consisted of acinetobacter, but contained various other species. There is no mycobacteria sequence identified, although there is actinobacterium sequence identified, which may be the mycobacteria.

Interpretation:

Because the biofilm was grown in a nonsterile environment, there were expected to be other species present in the biofilm to closely simulate household water system conditions. However, 16s sequencing is limited to bacterial species, and does not provide full insight into the community structure of the biofilm.

RNA-Seq Meta-Analysis

Overarching Goal: To identify differentially expressed genes and pathways in chassis organisms by comparing laboratory versus environmental transcriptomic and metatranscriptomic data

Experiment 11a:

Analysis of transcriptomic data comparing laboratory versus environmental samples

Raw Data:

DESeq2 Outputs from Galaxy workflow and literature DE gene datasets.

Data Analysis/Interpretation:

Differential expression analysis showed transcriptional changes between lab and environmental conditions. These results emphasize the importance of designing chassis with environmental adaptation in mind.

Experiment 11b:

Analyzing differences between metagenomic and metatranscriptomic taxonomic results

Raw Data:

Final outputs of running our comparison pipeline (metaG_metaT)

Figure: Taxonomic results of running metagenomic and metatranscriptomic FASTQ files.

Data Analysis/Interpretation:

The comparison reflects the yield differences between a metagenomic and metatranscriptomic processing done in the sample location from a singular study. This result reflects the importance of running both metagenomic and metatranscriptomic sequencing to understand both historical and current species presence within a sampling location.

Experiment 11c:

Functional analysis of DE genes

Raw Data:

Complete DAVID functional analysis output, unfiltered

Data Analysis/Interpretation:

After applying a Benjamini-Hochberg correction (α = 0.05), we observed a number of significant p-values, but relatively fewer adjusted p-values meeting the cutoff. Nonetheless, the pathways that did remain significant, primarily related to stress response, membrane transport, and metabolic adaptation aligned with those identified through AI-assisted analyses. These correlations suggest that our meta-analysis is capturing biologically meaningful trends, though further data expansion and processing are needed to strengthen statistical power and confirm emerging patterns.

Experiment 11d/e:

Al analysis of DE genes & Curation and Vetting of AI results

Summary Results:

Differentially Expressed Genes When Comparing Bacterial Gene Expression in the Lab vs Natural Aquatic Environments

Here we present summary results for differentially expressed genes when comparing bacterial gene depression in laboratory conditions and in natural aquatic environments.

Summary Results:

Differentially Expressed Genes When Comparing Bacterial Gene Expression in the Lab vs Natural Aquatic Environments

Here we present summary results for differentially expressed genes when comparing bacterial gene depression in laboratory conditions and in natural aquatic environments.

Whole-transcriptome shifts in natural waters

Seawater vs. lab exponential growth (E. coli): After 20 h in seawater, ~937 genes were upregulated and ~~320 downregulated relative to lab medium; stress and starvation programs dominated the response (microarray). This shows broad re-wiring away from growth programs you typically assume in the lab.

Global regulators override engineered promoters in the wild

Global stress regulators (e.g., RpoS/stringent response) gate expression when nutrients or conditions fluctuate—common in lakes/estuaries—so payload promoters that look “constitutive” in rich media can attenuate or become heterogeneous in situ. Recent reporter libraries that track multiple E. coli global regulators over time are useful references to explain these shifts.

Inducible systems behave differently outside the flask

Arabinose (PBAD) “all-or-none” induction: intermediate inducer levels create mixed ON/OFF subpopulations; fixing uptake (araE overexpression) yields more homogeneous induction—but in aquatic settings, uneven inducer diffusion/consumption often re-creates heterogeneity, weakening engineered outputs.

Cross-talk & performance drift: Work improving PBAD compatibility with IPTG (AraC evolution) underscores how inducer mixtures affect circuits; such mixtures and degradations are typical in environmental water, not in lab broth.

Community interactions and quorum effects

In mixed aquatic communities, quorum signaling and quorum-quenching alter transcription of motility, biofilm, nutrient uptake and public-goods genes—this cross-talk can silence or mis-time engineered outputs that looked clean in monoculture. Reviews focused on marine systems and WWTPs document these QS-mediated expression changes.

"Bottle effects” & sampling artifacts

How you collect the sample changes the expression you measure. A comparison of traditional Niskin bottle collection vs. in situ filtration showed different community gene-expression profiles, highlighting that ex-situ handling can distort conclusions about “field” expression of engineered strains.

Plasmid retention & engineered-gene stability drop without selection

In the lab, antibiotics/auxotrophies maintain plasmids; in natural waters, no selection → rapid plasmid loss or mutation, reducing reporter/cargo expression. Multiple methodological studies quantify higher plasmid loss rates without selection and discuss stabilization strategies (TA modules, CRISPRi-based maintenance, antibiotic-free systems)—all relevant because environmental release removes antibiotic selection.

Real-world aquatic microcosm tests of engineered reporters

GFP-tagged E. coli microcosms in freshwater/marine-like conditions showed reduced persistence and signal vs. lab culture, with survival and detectable fluorescence dropping over time—consistent with stress-driven and plasmid-loss explanations.

Engineered biosensors deployed in untreated water samples often require adapting induction/assay protocols because inducer availability and matrix effects blunt reporter expression (e.g., lead/PFOA biosensors).

Overall: There is lower mean expression, more heterogeneity, and time-dependent drift in natural waters, driven by stress responses, QS cross-talk, and plasmid/circuit instability. Characterization in realistic matrices (filtered lake/sea water, defined low-nutrient media, redox/UV cycles) + field-mimicking induction schemes is essential before in situ use. Reviews on environmental deployment and genetic-stability design patterns summarize practical strategies (kill-switches, metabolic load reduction, chromosomal integration, resource-insulated parts).

Environment-enriched (often ↑ in seawater/soil/hosts/particles vs LB/glucose lab)

Iron scavenging (Fe-limitation)

tonB–exbB–exbD (energize OM receptors), OM receptors fepA/cirA/fecA/fhuA/fpvA/hasR, siderophores entCEBA (enterobactin), pvd/pch (pyoverdine/pyochelin), dhb (bacillibactin).

Phosphate starvation (Pho regulon)

High-affinity uptake pstSCAB, regulators phoBR/phoPR, phosphatases phoA/phoD, organo-P phn (phosphonate).

Nitrogen & sulfur scavenging

amtB–glnK (NH4+), nitrate/nitrite narGHI/nirBD/nas, taurine/alkanesulfonate ssuEADCB, tauABCD.

Osmoprotection / desiccation

Release valves mscL/mscS, compatible solutes uptake proU/proVWX, opuA/opuC/opuD, synthesis betT–betIBA (GB), ectABC (ectoine), otsAB (trehalose).

Oxidative/UV stress defenses

Peroxide/superoxide: katG/katE, sodA/sodB, ahpCF, dps, msrA/B, trxA/B, gor; DNA repair uvrABC, phr, recA. Regulators oxyR/soxRS, perR, sigB.

Motility & chemotaxis (foraging)

Flagella program flhDC/fliA/fli, chemotaxis cheA/cheY and MCPs, motors motA/motB.

Adhesion/biofilm & surface sticking

Gram-: EPS/export wza/wzc/wzb, curli csg, pel/psl/algD (Pseudomonas). Gram+: epsA-O, tapA–sipW–tasA (Bacillus). Often under QS: luxS/AI-2, las/rhl/pqs, aphA/opaR (Vibrio).

Broad substrate uptake & catabolism

ABC/TRAP/outer porins (dctPQM, dctA, oprD), complex carbon: aromatic ring cleavage ben/cat/pca, chitin/cellulose/hemicellulose hydrolases (chiA/chb, celAB, xylAB).

Membrane remodeling for stress

FA tuning: desA/desC (desaturases), cfa (cyclopropane FA), hopanoids hpn (e.g., Z. mobilis).

Defense & phage pressure

CRISPR–Cas, RM systems, toxin–antitoxin (mazEF, relBE).

Competence / gene exchange (in situ cues)

comEA/EC/FA (Gram+), type IV pili/pilus assembly; tfoX/Y (Vibrio on chitin).

Storage polymers

ppk/ppx (poly-P), glycogen glgABC, PHB phbCAB.

Lab-enriched (often ↑ in rich, aerated exponential culture)

Fast growth / translation machinery

rRNA operons rrn, ribosomal proteins (rpl, rps), tRNA synthetases, elongation factors fusA, tufA/B.

Central carbon for rapid glycolysis

ptsG/manXYZ (PTS sugar uptake), pgi/pfkA/pykF, TCA/respiration modules; overflow pta–ackA, ldhA (acetate/lactate).

Amino acid & nucleotide biosynthesis

ilv/leu/aro, pur/pyr (especially in minimal but nutrient-replete growth).

Cell division & envelope biogenesis

ftsZ/ftsA/zipA (divisome), mur/fab (peptidoglycan/FA biosynthesis), LPS core/synthesis in Gram-.

Housekeeping chaperones (heat shock during fast growth)

rpoH (σ32), dnaKJ, groESL, ibpAB.

Motility/Biofilm OFF

Many lab conditions repress costly flagella/EPS; QS modules often low.

Using Differentially Expressed Gene Lists to Suggest Engineering Approaches to Make Engineered Chassis Fieldable in Aquatic Systems

Here we provide genes and target modules that repeatedly show in situ up-regulation in natural aquatic environments as well as down regulated in natural aquatic environments — and suggestions on what to engineer. Below are practical edit ideas associated with pathways known to flip between lab and field. We list gene families (examples) and why they matter in water.

Using Differentially Expressed Gene Lists to Suggest Engineering Approaches to Make Engineered Chassis Fieldable in Aquatic Systems

Up-Regulated in Aquatic Environments:

Membrane fluidity & pressure/cold adaptation

Desaturases (desA/desC, fabA/fabB regulators), cyclopropane synthase (cfa), Psp stress operon: tune unsaturated/cyclopropane fatty acids to keep membranes functional under cold/high hydrostatic pressure. Overexpress desaturases; inducible cfa for transient shocks.

Chassis tip: Shewanella piezotolerans/baltica show clear transcript shifts under cold/HHP; their parts and promoters are a great starting library.

Osmoregulation & ion balance (salinity swings)

Compatible solute synthesis/transport: ectoine (ectABC), glycine betaine transporters (proVWX, betT/betAB), mechanosensitive channels (mscL/mscS). Install tunable uptake + synthesis; add an osm promoter to couple growth to external salinity profiles (marine ↔ brackish).

Light & photoprotection (surface waters, algae/cyanobacteria)

NPQ/photoprotection modules in diatoms and algae: LHCX family (e.g., lhcx1/2), carotenoid cycle genes. LHCX2 responds sensitively to iron limitation; wire this to a promoter reporting Fe stress to regulate antenna size or repair.

DNA photolyase (phr), uvrABC excision repair: upweight for high UV.

Nutrient scavenging at oceanic concentrations

Phosphate: pstSCAB, phoBR regulon; Iron: TonB-dependent receptors, siderophore uptake; diatom Fe-inducible loci (e.g., ISIP1, co-expressed with LHCX2 under Fe limitation). Overexpress high-affinity transporters; use riboswitches for dynamic uptake.

Nitrogen: amtB (NH4+), urea (ureABCDEFG), cyanate (cynS), nitrate/nitrite transporters; glnB (PII) links C–N balance in cyanobacteria—use as a sensor or controller node for C/N flux.

Oxidative stress & UV-derived ROS

Peroxiredoxins (ahpC), catalase-peroxidase (katG), superoxide dismutases (sodA/sodB), thioredoxin systems. Build a layered ROS defense with a fast peroxide sensor controlling membranes and repair enzymes.

Community interactions: competition, cooperation, viruses

Bacteriocin/bacteriocin-like peptides & export: Prochlorococcus co-culture DEGs reveal small exported peptide families (e.g., CCRG genes) induced by neighbors—use such motifs for programmable interference or communication.

Quorum sensing (LuxI/LuxR) wired to resource uptake or motility; biofilm/EPS (e.g., wza/wzc, pel/psl) for particle/surface association at the right time.

Phage defense: CRISPR-Cas, BREX/DISARM as swappable cassettes to harden open-water deployments.

Motility & microscale foraging

Chemotaxis/flagella (cheA/cheY, motAB, fli genes): program “forage and settle” behaviors—chemotaxis on labile DOM or phosphate gradients, then EPS-mediated attachment.

Down-Regulated in Aquatic Environments:

High-rate translation & ribosome biogenesis

Genes/modules: rrn rRNA operons; ribosomal proteins (rpl/rps loci), translation factors (tufA/B, fusA, tsf, infA/B/C), tRNA synthetases. Slow growth dominates in oligotrophic waters; the stringent response ((p)ppGpp) suppresses rRNA/tRNA and ribosome biogenesis, shifting resources to stress survival. Growth-law work shows ribosome fraction scales with growth rate, so low μ in the field ⇒ low ribosome program.

DNA replication initiation & cell division

Genes/modules: Initiation/elongation (dnaA, dnaN, dnaG, gyrA/B), divisome (ftsZ, ftsA, zipA, ftsQLB).

Why down in situ: Nutrient limitation triggers (p)ppGpp-mediated suppression of replication initiation; explicit starvation studies in Vibrio show replication initiation shut-off during stringent response. With slower cycles, division genes fall too.

PTS sugar uptake & lab-sugar catabolism

Genes/modules: PTS core (ptsH/ptsI/crr), glucose PTS (ptsG), mannose PTS (manXYZ), lab sugar regulons (lac, mal, etc.).

Why down in situ: In the ocean, ABC/SBP transport dominates (high-affinity scavenging) while PTS is rare/inefficient at nM substrates; copiotrophs that carry PTS down-shift it in low-nutrient seawater. Comparative genomics & theory show an ABC↔PTS rate-affinity tradeoff underlying oligotroph vs copiotroph lifestyles.

Overflow metabolism (acetate/lactate “Crabtree-like”)

Genes/modules: pta–ackA (acetate), poxB (pyruvate oxidase), ldhA (lactate).

Why down in situ: Overflow pathways are hallmarks of glucose-rich, aerated lab growth; under carbon-limited seawater they’re unnecessary and typically repressed.

Flagellar assembly & motility (pelagic starvation context)

Genes/modules: Master/flagella (flhDC, fliA, fliC), motors (motA/B), chemotaxis (cheA/cheY).

Why down in situ: Under prolonged starvation in seawater, several vibrios damp flagellum assembly to save ATP; motility often re-emerges near particles/blooms (exception).

Low-affinity phosphate transport (Pi-replete lab bias)

Genes/modules: Pit system (pitA, pitB) vs high-affinity PstSCAB–PhoU.

Why down in situ: In low-P waters, cells induce Pst and Pho regulon while low-affinity Pit is disfavored/curtailed; Pit tends to operate under Pi-replete lab conditions.

Heat-shock (σ³²/RpoH) program at 37 °C

Genes/modules: rpoH (σ³²), chaperones dnaKJ, groESL, proteases (hslUV, lon, ftsH).

Why down in situ: Ambient seawater (~4–25 °C) rarely triggers the RpoH/heat-shock axis that is prominent at 30–37 °C lab growth; cold-shock modules may be used instead.

Core, conserved toolbox (works across many bacteria)

Osmotic shock / salinity

Release valves: mscL, mscS → OE (low-leak) to prevent lysis in rapid hypo-osmotic dips.

Compatible solutes (uptake & synthesis): betT, betIBA (choline → glycine betaine), proVWX/proU (GB/Pro uptake), opuA/opuC (Firmicutes), opuD (GB uptake), ectABC (ectoine), gbsAB (GB synthesis in Gram+).

→ REG by salinity/σ^S/σ^B or QS; preload pools for shocks.

Iron acquisition (Fe-poor)

Energy for outer-membrane receptors: tonB–exbB–exbD → mild OE (1–2×).

Siderophore biosynthesis/uptake (species-specific) + OM receptors (fepA/cirA/fecA/fhuA, fpvA, etc.) → REG by Fe limitation (Fur/PerR logic) with guardrails vs. ROS.

ROS/UV

Peroxides/•OH/superoxide: katG/katE, sodA/sodB, ahpC/ahpF, trxA/trxB, gor → basal OE of katG/sodA, stress-inducible ahpC/trx.

DNA repair: uvrABC, phr, recA → constitutive/UV-inducible.

Regulators: OxyR/SoxRS (Gram-), PerR/SigB (Gram+).

Phosphate scavenging

pstSCAB–phoBR (Gram-) / pstSCAB–phoPR (Gram+) → REG via Pho promoters for low-P; add phoA/phn where organo-P needed.

Membrane tuning / motility & sticking

FA remodeling: desA/desC (desaturases), cfa (cyclopropane FA) → OE or REG (cold/pressure/solvent); avoid over-stiffening.

Motility: flhDC (master), cheA/cheY, motA/motB → REG/QS toggle for particle-association vs. free-living.

EPS/export: wza/wzc/wzb (Gram-), eps/tapA–sipW–tasA (Bacillus matrix), pel/psl (Pseudomonas).

General stress programs

rpoS (σ^S) in many Gram-, sigB (σ^B) in Firmicutes → REG to gate costly defenses.

Heat/cold shock: rpoH (σ³²), groESL, dnaKJ, ibpAB, cspA → inducible modules.

Aquatic Laboratory vs Environment Differential Gene Expression

Specific Case Study: Bacillus subtilis

Here we present a summary of genes differentially regulated between lab and natural aquatic systems, and potential engineering approaches to enhance survival and persistence, of Bacillus subtilis in natural environments, for one of our case studies: the use of Bacillus subtilis to prevent or at least diminish corrosion.

Specific Case Study: Bacillus subtilis

Field-mode priorities (environment-enriched engineering levers)

Osmotic shock & salinity

Knobs: opuA / opuC / opuD (GB/carnitine uptake), gbsAB (choline→glycine betaine), ± ectABC (ectoine; heterologous or native if present), MS channel yfkC (MscS-like).

Why field-up: Freshwater/estuarine microbes see rapid hypo-osmotic dips (rain/runoff) and patchy salt. Opu uptake fills compatible-solute pools fast; GbsAB converts choline to GB when available; ectoine is a high-value osmolyte for chronic salt/ desiccation; YfkC dumps solutes on sudden dilution to prevent lysis.

Suggestions: REG (salinity/σ^B): put opu and gbsAB under a σ^B or salt-responsive promoter; run yfkC at low-leak OE for “airbags always armed” without chronic leak. Optional: add ectABC(+ask) under a salt switch for brackish deployments. Guardrails: Too-high Opu overfills cytosol (viscosity/growth cost). Cap max expression; consider a “salinity AND growth” gate (e.g., σ^B AND growth-on).

Iron acquisition (Fe-poor water)

Knobs: dhbACEBF (bacillibactin synthesis), feuABC (bacillibactin uptake), fhuBGC (ferrichrome), other TBDRs; feoAB (Fe²⁺ under microoxia); regulator fur (Fur).

Why field-up: Dissolved Fe is picomolar-nanomolar in many waters; siderophore biosynthesis/uptake dominates.

Suggestions: REG (Fe-limitation): drive dhb/feu/fhu from native Fur-repressed promoters (Fe-OFF = ON). Light OE of feoAB for hypolimnia/low O₂. ROS guardrails: Couple Fe-uptake to PerR/σ^B outputs (e.g., Oxy-like NOT gate) to avoid Fenton overload when H₂O₂ spikes. Pitfalls: Siderophore overproduction is metabolically pricey; use ceilings and OFF in Pi-replete, Fe-replete lab phases.

ROS & redox control (surface waters, metal-rich particles)

Knobs: katA (major vegetative catalase), katE (secondary), sodA, ahpCF, trxA/B, tpx, storers dps. Regulators: perR (peroxide), sigB (general stress), Spx (thiol-stress).

Why field-up: UV/light and metal recycling on particles drive H₂O₂ / O₂⁻ pulses; Bacillus relies on PerR (OxyR analog) and σ^B.

Suggestions: Basal OE: small katA / sodA baseline. Inducible: put ahpCF / tpx / trx on PerR- or σ^B-responsive promoters. Add a “redox fuse”: an Spx-activated kill-switch ceiling to avoid runaway ROS when Fe uptake is high. Pitfalls: Over-catalase can blunt oxidative signaling needed for acclimation; keep basal OE mild.

UV/DNA damage repair (sunlit epilimnia)

Knobs: phr (photolyase), uvrA/B/C (NER), recA.

Why field-up: Direct UV photoproducts in surface waters.

Do this: Constitutive low phr + UV-inducible NER. For dark deployments (hypolimnion/groundwater), keep them native to save energy.

Phosphate scavenging (low-P lakes & particles)

Knobs: pstSCAB–phoPR (Pho regulon), phoA / phoD (secreted alkaline phosphatases), ± phosphonates (phn operon), cell-wall remodeling tuaABCDEFG (teichuronic acid synthesis under Pi limitation).

Why field-up: Pi is often limiting; Bacillus replaces wall teichoic acids with teichuronic acids to spare phosphate.

Do this: REG (Pho): use P_pstS / PhoPR-responsive promoters to drive high-affinity uptake and phoD secretion. Include tua under Pho to lock in the low-P envelope program (less Pi in the wall = more for growth). Pitfalls: Over-secretion of AP can be costly; meter via Pho activity reporter.

Sulfur & nitrogen scavenging (DOM-rich, sulfate/nitrate limited)

Knobs (S): ssuEADCB (alkanesulfonates), tauABCD (taurine).

Knobs (N): nasABC (assimilatory nitrate), nirBD (nitrite→NH₄⁺), regulators TnrA/GlnR.

Why field-up: Inorganic S/N can be scarce; organosulfur and nitrate/nitrite pulses are common.

Suggestions: put ssu/tau behind sulfur-limitation logic (CysB-like) and nas/nir behind TnrA-ON (N-limitation) to widen usable nutrient space.

Membrane fluidity & cold adaptation

Knobs: des (Δ5 desaturase), bkd (branched-chain FA precursor supply), fabF/B tuning.

Why field-up: Homeoviscous adaptation for cold/pressure; branched FAs in Gram+ modulate membrane rigidity.

Do this: Mild REG of des for cold regimes; upweight bkd for more iso/anteiso FAs in chill/low-energy deployments. Pitfalls: Over-desaturation can impair growth at moderate temperatures.

Motility/chemotaxis ↔ biofilm/matrix toggle (foraging vs sticking)

Motility knobs: sigD (σ^D master), fli/flg structural genes, cheA/cheY, motA/B.

Matrix knobs: epsA–O (EPS), tapA–sipW–tasA (amyloid fibers), bslA (hydrophobin).

Why field-up: Two modes matter: swim to find patches; stick to exploit particles/surfaces.

Suggestions: Build a QS/σ^B/energy-aware toggle: when carbon high + shear low → matrix ON (EPS/tasA/bslA); when carbon low/shear high → motility ON. Use the native regulators: Spo0A–SinI/SinR–SlrR–DegU to flip states cleanly (avoid half-on burden). Pitfalls: Matrix constitutive OE tanks growth in pelagic starvation; keep conditional.

Sporulation (last-ditch survival)

Knobs: spo0A (master) + phosphorelay; Rap phosphatases.

Why field-relevant: True long-term survival; but not your default “field-mode growth”.

Suggestions: Keep sporulation competence intact but raise the threshold: e.g., require multi-input AND (carbon starvation + oxidative + high cell age). Provide a recovery path (germination genes) for lab passage. Pitfalls: Don’t accidentally wire everything to Spo0A and lock growth.

Lab-biased programs (make switchable or down-tuned in field mode):

High-rate translation & ribosome biogenesis

Knobs: rrn operons; ribosomal proteins (rpl/rps); tuf/fus/tsf/inf.

Why lab-up / field-down: Low specific growth rates in situ (stringent response) → less rRNA/tRNA/ribosome demand.

Engineering: Keep native control; if you use growth boosters in the lab, ensure hard OFF in field mode (ppGpp-sensitive promoters are your friend).

DNA replication & cell division

Knobs: dnaA/dnaN, gyrA/B, ftsZ/ftsA/sepF, divIC/ftsL.

Why lab-up: Rapid lab growth demands strong replication/division; in the field, cells pace themselves.

Engineering: Avoid constitutive overdrive; let starvation/dormancy signals suppress the divisome.

PTS sugar uptake (simple lab sugars)

Knobs: ptsG, ptsH (HPr), ptsI (EI), manP (mannose PTS).

Why lab-up: PTS excels at high-flux glucose; natural DOM is dilute/complex → ABC/TRAP + SBPs are favored.

Engineering: Make PTS inducible for lab scale-up; default OFF in field mode.

Overflow metabolism (acetate/lactate)

Knobs: pta–ackA (acetate), ldh (lactate), poxB (pyruvate oxidase).

Why lab-up: Shake-flask, sugar-rich conditions; in situ carbon limitation doesn’t support overflow.

Engineering: Keep repressible; favor full respiration/fatty-acid use in field mode.

Heat-shock programs prominent at 30–37 °C

Knobs: HrcA regulon (dnaKJ, groESL, grpE), CtsR (clpC/P).

Why lab-up: Lab temperatures trigger these; ambient waters often activate cold/oxidative, not heat shock.

Engineering: Keep inducible; avoid high basal load in field mode.

Low-affinity phosphate transport

Knobs: pitA (if present).

Why lab-up: Works fine in Pi-replete lab media; disfavored in low-P waters where Pst dominates.

Engineering: De-emphasize; rely on Pst/PhoPR.

Summary: Bacillus subtilis 168 Lab biased (down tune in field)

High rate translation & ribosome biogenesis

Genes: rrn operons; rpl*/rps*; tufA; fusA; tsf; infA/B/C

Field Action: Default OFF in field; inducible for lab scale up

Bench Promoter: Inducible bench promoters (IPTG/xylose)

Hints: ppGpp/CodY on in field

Guardrail: Avoid energy/proteome drain in oligotrophy

Why: Lab programs elevated in rich, aerated culture

DNA replication & cell division

Genes: dnaA/dnaN; gyrA/B; ftsZ/ftsA/sepF; divIC/ftsL

Field Action: Default OFF in field; inducible for lab scale up

Bench Promoter: Inducible bench promoters (IPTG/xylose)

Hints: ppGpp/CodY on in field

Guardrail: Avoid energy/proteome drain in oligotrophy

Why: Lab programs elevated in rich, aerated culture

PTS sugar uptake (simple lab sugars)

Genes: ptsG; ptsH; ptsI; manP

Field Action: Default OFF in field; inducible for lab scale up

Bench Promoter: Inducible bench promoters (IPTG/xylose)

Hints: ppGpp/CodY on in field

Guardrail: Avoid energy/proteome drain in oligotrophy

Why: Lab programs elevated in rich, aerated culture

Overflow metabolism (acetate, lactate)

Genes: pta ackA; ldh; poxB

Field Action: Default OFF in field; inducible for lab scale up

Bench Promoter: Inducible bench promoters (IPTG/xylose)

Hints: ppGpp/CodY on in field

Guardrail: Avoid energy/proteome drain in oligotrophy

Why: Lab programs elevated in rich, aerated culture

Heat shock regulons at 30–37 °C

Genes: hrcA (dnaKJ, groESL, grpE); ctsR (clpC/P)

Field Action: Default OFF in field; inducible for lab scale up

Bench Promoter: Inducible bench promoters (IPTG/xylose)

Hints: ppGpp/CodY on in field

Guardrail: Avoid energy/proteome drain in oligotrophy

Why: Lab programs elevated in rich, aerated culture

Case Study: Acinetobacter baylyi ADP1

Here we present a summary of genes differentially regulated between lab and natural aquatic systems, and potential engineering approaches to enhance survival and persistence, of Acinetobacter baylyi ADP1 in natural environments, for one of our case studies: the use of Acinetobacter baylyi ADP1 to remediate HABS.

Case Study: Acinetobacter baylyi ADP1

Here we present a summary of genes differentially regulated between lab and natural aquatic systems, and potential engineering approaches to enhance survival and persistence, of Acinetobacter baylyi ADP1 in natural environments, for one of our case studies: the use of Acinetobacter baylyi ADP1 to remediate HABS.

Acinetobacter baylyi ADP1 suggested to up tune in field:

Osmoprotection

ADP1 uses BCCT transporters (e.g., ACIAD3460) for glycine betaine; it has osmo-dependent and osmo-independent choline transporters; GB uptake improves high-salt survival.

Choline→GB & regulation

betIBA and two BetT-like routes (osmo-independent BetT1 vs. osmo-dependent BetT2) described; wiring them to salinity/choline sensors matches physiology.

Aromatic DOM catabolism

Native β-ketoadipate island (ben/cat/pca; pobA; BenM/CatM/PcaU) is a hallmark of ADP1 and is routinely up when aromatic substrates are present.

Fe acquisition

In Acinetobacter spp., iron uptake relies on TonB–ExbB–ExbD and numerous TBDRs; A. baumannii uses acinetobactin, while ADP1 is generally viewed as a non-pathogenic environmental strain that can pirate exogenous siderophores—so emphasize TBDRs/Feo and Fur-logic rather than siderophore biosynthesis. (Inference drawn from genus-level reviews + ADP1 genome resources.)

ROS/UV & DNA repair

ADP1 shows ROS-linked responses under oxidative/biocide stress; pair catalases/SOD with PerR-like peroxide defenses and NER/photolyase for surface waters.

Outer-membrane porins

Nutrient vs. toxin influx trade-offs (OmpA/CarO/OprD-like) documented for Acinetobacter; use modest, context-dependent tuning.

Lab-biased storage lipids

ADP1’s wax ester pathway (atfA, acr1) is prominent under high C/N in the lab—handy for production, but usually a carbon sink in dilute waters.

Domestication context

Recent work catalogs lab domestication mutations in ADP1 that alter competence, carbon use, and aggregation—useful when reconciling lab vs. field behavior.

Acinetobacter baylyi ADP1 Lab biased/upregulated (suggested to down tune in field)

High rate translation & ribosome biogenesis

Genes: rrn operons; rpl/rps; tuf/fus/tsf/inf

Field Action: Keep native control; repress in field via ppGpp; lab only induction

Bench Promoter: Inducible bench promoters

Hints: ppGpp ON in field

Guardrail: Proteome burden in oligotrophy

Why: Ribosome fraction tracks growth rate

DNA replication & cell division

Genes: dnaA/dnaN; gyrA/B; ftsZ/ftsA/zipA/sepF

Field Action: Avoid constitutive OE; allow starvation/dormancy to suppress divisome

Bench Promoter: Inducible only

Hints: Starvation sensors gate OFF

Guardrail: Division push causes stress in dilute waters

Why: Replication/division downshift during limitation

PTS/simple sugar shortcuts

Genes: PTS core (if present) + high flux glycolysis

Field Action: Default OFF in field; prefer high affinity ABC/SBPs

Bench Promoter: Induce with lab sugars only

Hints: Carbon limitation gates OFF

Guardrail: Inefficient at nM sugars

Why: Natural DOM is dilute/complex

Overflow metabolism

Genes: acetate/lactate routes

Field Action: Keep OFF in field; favor respiration

Bench Promoter: Carbon/oxygen sensors

Hints: Repress when C limited

Guardrail: Low yield without benefit

Why: Overflow is lab artifact of high carbon + aeration

Heat shock at 30 37 °C

Genes: dnaKJ; groESL; grpE; clpC/P (HrcA/CtsR)

Field Action: Keep inducible; avoid high basal at ambient water temps

Bench Promoter: Native heat shock promoters

Hints: Only when >30 37°C

Guardrail: Chronic load taxes proteome

Why: Field programs skew to cold/oxidative

Specific Case Study: Mycobacterium smegmatis

Although we are using phage to remediate Mycobacteria biofilms in pipes, there is insufficient information regarding phage behavior of phage in laboratory and natural environments. Therefore we present gene analysis between page behavior in laboratory and natural environments. Here we present a summary of genes differentially regulated between lab and natural aquatic systems, and potential engineering approaches to enhance survival and persistence, of Mycobacteria smegmatis in natural environments, for one of our case studies: the use of mycobacteria phage to destroy mycobacterial biofilms in household plumbing. This is still relevant given that the biofilms may likely behave differently in actual aquatic (household plumbing) environments compared to laboratory settings.

Specific Case Study: Mycobacterium smegmatis

Below is a list of modules that are up repeatedly up in natural waters vs lab that are good targets to overexpress and modules that are typically down in natural waters which are good to reducing expression.

Environment-enriched modules

Iron acquisition (Fe-poor water)

Mycobactin / carboxymycobactin biosynthesis: mbt clusters (mbtI–mbtN). Action: REG by low-Fe (IdeR-off); mild OE ceiling. Why: core siderophores for Fe capture.

Exochelin pathway (M. smegmatis-specific): fxbA (+ exochelin biosynthetic/transport genes). Action: REG by low-Fe (IdeR-off). Why: additional extracellular siderophore in M. smegmatis.

Siderophore import/reduction: irtAB (inner-membrane ABC importer; reduces Fe-cMBT). Action: OE 1–2× with low-Fe promoter.

Type VII secretion for Fe uptake: ESX-3 locus (esxG/H, ecc, mycP3, etc.). Action: keep REG by Fe/Zn; avoid KO. Why: required for mycobactin-mediated iron acquisition.

Regulator: IdeR (DtxR-family). Action: keep intact; use IdeR-responsive promoters for “Fe-on” logic. Why: master Fe homeostasis; couples Fe uptake with oxidative stress defenses.

Outer access

MspA/MspC porins. Action: OE mspA (± mspC) to raise solute/Fe flux; use native σ^A promoter or stress-tunable. Why: major hydrophilic conduit; porin loss reduces Fe/phosphate/glucose uptake.

Phosphate scavenging (P-poor water/particles)

High-affinity transport: pstSCAB–phoU1/phoU2. Action: REG via the SenX3–RegX3 system; avoid constitutive OE. Why: dedicated low-P uptake; two PhoU paralogs tune signaling.

Aux systems under low P: phnDCE (phosphonate). Action: REG by low-P; pair with P starvation reporters.

Carbon/osmoprotection tied to the mycomembrane

Trehalose recycling/uptake: LpqY–SugABC; treS, otsA/otsB for trehalose metabolism. Action: REG by stress; consider OE of LpqY–SugABC to save ATP in envelope turnover; “field-mode” trehalose pool.

Mechanosensitive channel (osmotic dips): mscL (and MscS-like homologs). Action: keep a low-leak OE baseline. Why: emergency solute dump under hypo-osmotic shocks.

ROS & redox defenses (surface waters / metal stress)

Peroxides & superoxide: katG (I/II/III), sodA, ahpC/D, tpx, trx/gor. Action: basal OE of katG/sodA; put ahpC/tpx under ROS-inducible control. Why: M. smegmatis encodes multiple katG; ROS stress strongly induces this axis.

Hypoxia / energy limitation (stratified lakes, biofilms)

Dormancy/hypoxia regulon: dosR–dosS/dosT ± PrrAB cross-talk. Action: keep DosR circuit intact; you can drive “low-O₂ mode” cassettes from DosR targets. Why: essential for hypoxic survival; stabilizes ribosomes.

Envelope remodeling / permeability (nutrient-poor water)

Porins: mspA/mspC OE as above. Why: improves influx of hydrophilic solutes/Fe.

Mycolic-acid desaturation: desA1, desA2 (regulated by MadR). Action: REG to tune fluidity; modest OE for cold/low-energy regimes; avoid over-stiffening. Why: desaturation is essential; MadR links envelope stress to desA1/2.

Cyclopropanation/methyltransferases: cmaA1/2, pcaA, mmaA1/2. Action: REG/KO to adjust permeability vs robustness; (pathogenesis-linked effects mostly from Mtb, but orthologs inform tuning in M. smegmatis).

GPL biosynthesis & export: mps/tmtpC/gpl cluster, mmpL11; groEL1 assists biofilm matrix. Action: REG by surface cues; OE to increase sticking when desired. Why: GPL acetylation affects sliding/biofilm; mmpL11 exports MA-lipids needed for biofilm.

Lab-enriched modules (often down in natural waters)

High-rate translation & ribosome biogenesis

rrn, rpl/rps, EF/Tu (tuf), EF-G (fus). Action: make repressible in “field mode.” Why: slow growth in situ; stringent response suppresses these. (General growth-law logic; also reflected under DosR programs in mycobacteria.)

DNA replication/division

dnaA/dnaN, ftsZ/ftsA/zipA. Action: avoid constitutive overdrive; keep native control for low-μ. (DosR-linked dormancy reduces replication pressure.)

Heat-shock at 30–37 °C (classic lab temps)

dnaKJ, groEL/ES (keep but don’t force high basal expression for field mode). Why: ambient waters rarely trigger strong heat-shock; oxidative/cold responses dominate. (General)

Low-affinity phosphate transport

pitA/B (when present). Action: prefer PstSCAB–PhoU–RegX3 under low-P; avoid Pit-only reliance.

Overflow pathways (acetate/lactate) from sugar-rich shake flasks

Prefer respiration/fatty-acid utilization in field mode; don’t hard-wire pta–ackA/ldhA overflows. (General lab-bias.)

Overall Summary:

Mycobacterium smegmatis Field mode (environment enriched)

Iron acquisition (mycobactin/exochelin)

Genes: mbtI mbtN (mycobactin/cMBT); fxbA (exochelin biosynth/transport); irtAB (siderophore import/reduction); ESX 3 (esxG/H, ecc, mycP3); IdeR (regulator)

Action: REG siderophore biosynth/import by low Fe; keep ESX 3 intact; mild OE irtAB

Promoter: IdeR OFF promoters (Fe limitation); ESX 3 native promoters

Hints: Fe sensor (IdeR OFF) AND ROS LOW gate

Guardrail: Couple Fe uptake to ROS LOW to avoid Fenton overload

Why: Core Fe capture in dilute waters; ESX 3 required for mycobactin Fe use

Outer permeability porins

Genes: mspA, mspC

Action: Moderate OE (tunable promoter) to increase hydrophilic influx

Promoter: A like constitutive or mild inducible

Hints: Cap expression; combine with toxin sensitivity monitor

Guardrail: Higher porin levels increase antibiotic/toxin influx cap OE

Why: Porins dominate small solute entry; boosts Fe/P/glucose uptake in poor media

Phosphate scavenging

Genes: pstSCAB phoU1/phoU2; SenX3 RegX3 (Pho control); phnDCE (phosphonate)

Action: REG Pst via RegX3; enable phosphonate transport when Pi scarce

Promoter: PpstS/Pho responsive promoters

Hints: Use Pho activity reporter to meter AP load

Guardrail: Avoid constant Pho ON burden from secreted enzymes

Why: Low P waters select high affinity uptake and phosphonate salvage

Trehalose recycling & metabolism (envelope/osmoprotection)

Genes: LpqY SugABC (trehalose uptake/recycling); treS; otsA/otsB

Action: REG stress responsive; OE LpqY SugABC to recover trehalose from envelope turnover

Promoter: Native trehalose module promoters; stress responsive logic

Hints: Cap trehalose pool with ceiling or drain

Guardrail: Trehalose overaccumulation can slow growth

Why: Saves ATP and supports mycomembrane maintenance/osmoprotection

Mechanosensitive channel (osmotic dips)

Genes: mscL (± MscS like)

Action: Low leak baseline OE

Promoter: Weak constitutive promoter

Hints: Leakage reduces turgor if too high

Guardrail: Avoid chronic leak

Why: Prevents lysis during rapid hypo osmotic shocks

Mycobacterium smegmatis Lab biased (down tune in field)

High rate translation & ribosome biogenesis

Genes: rrn operons; rpl/rps; tuf/fus/tsf/inf

Action: Keep native control; repress in field via ppGpp; lab only induction

Promoter: Bench: Pami (acetamide) / Tet; Field: stringent responsive rrn promoters

Hints: ppGpp sensor gate for OFF in field

Guardrail: Avoid proteome/ATP burden in oligotrophy

Why: Ribosome fraction tracks ; low in situ growth rates

DNA replication & cell division

Genes: dnaA/dnaN; gyrA/B; ftsZ/ftsA/zipA/ftsQLB

Action: Avoid constitutive OE; allow starvation/dormancy to suppress divisome

Promoter: Bench inducible (Pami/Tet); field OFF via starvation cues

Hints: Prevent filamentation/stress at low nutrients

Guardrail: Constitutive push stresses cells in dilute waters

Why: Replication/division are downshifted in natural waters

Heat shock program (30 37 °C bias)

Genes: dnaKJ; groEL/ES; hsp; proteases (lon, ftsH, clp)

Action: Keep inducible; avoid high basal in field

Promoter: Native heat shock promoters only

Hints: Reduce basal at ambient temps

Guardrail: Chronic load taxes proteome

Why: Field conditions emphasize cold/oxidative, not strong heat shock

Low affinity phosphate transport

Genes: pitA/pitB (if present)

Action: De emphasize; rely on Pst/RegX3 under low P

Promoter: Pho responsive control (PpstS)

Hints: Disable in Pi poor water

Guardrail: Pit inefficient at low Pi

Why: Low P environments select high affinity Pst

Overflow pathways (shake flask artifact)

Genes: pta ackA; ldhA (if present); poxB like routes

Action: Keep OFF in field; favor respiration and FA utilization

Promoter: Carbon/oxygen sensors; bench only inducible

Hints: Avoid acid stress/low yield in low C waters

Guardrail: Overflow gives low yield with little benefit in situ

Why: Overflow requires high sugar + aeration; uncommon in natural waters

Executive Summary

I. Marine Corrosion Prevention with Bacillus subtilis

II. Freshwater Harmful Algal Bloom (HAB) Remediation with Cyanophage and Acinetobacter baylyi

III. Biofilm Removal in Household Pipes Using Phage Therapy

Bioinformatics & RNA-Seq Meta-Analysis

Aquatic Case Study I:

Corrosion Prevention Using Engineered Bacillus subtilis in Marine Environments

Experiment 1:

Construction of Engineered B. subtilis Strains

Experiment 2:

Establishing growth curves to compare growth dynamics of B. subtilis 168, 3610, and the 4 engineered 168 variants under laboratory conditions

Experiment 3:

Evaluating the motility of B. subtilis 168, 3610, and the 4 engineered 168 variants

Experiment 4:

Determining effect of our genetic modifications on biofilm robustness and structure through characterization of biofilm and colony morphology of laboratory and engineered strains of Bacillus subtilis

Experiment 5:

Evaluating corrosion protection abilities of each strain on steel surfaces in a simulated marine environment

Experiment 6:

Analysis of gene expression differences between lab and microcosm environments in strains with strong corrosion protection

Aquatic Case Study II:

Freshwater Algal Bloom Remediation

Experiment 7:

Microcystis Cyanophage Isolation for Harmful Algal Bloom Remediation

Experiment 8:

Comparison of Acinetobacter baylyi Behavior in Laboratory vs Simulated Real-World Microcosms

Experiment 8a:

Estimating A. baylyi survival in microcosms and control cocultures via colony counts

Experiment 8b:

Quantifying species abundance in microcosms and control cocultures via 16S amplicon sequencing

Experiment 8c:

Quantifying differential gene expression of A. baylyi in microcosms and control cocultures via RNA sequencing

Aquatic Case Study III:

Removal of Biofilms in Household Pipes

Experiment 9:

Determining efficiency of specific mycobacteriophages to lyse mycobacteria under laboratory conditions

Experiment 10a:

Determining titer of viable bacteria in the microcosm effluent before and after phage infection

Experiment 10b:

Determining phage survivability in microcosm conditions

Experiment 10c:

Testing phage presence in microcosm effluent at the final time point

Experiment 10d:

Determining the structure of the biofilm in the pipe following phage treatment

Experiment 10f:

Determining bacterial community structure of microcosm biofilm

RNA-Seq Meta-Analysis

Experiment 11a:

Analysis of transcriptomic data comparing laboratory versus environmental samples

Experiment 11b:

Analyzing differences between metagenomic and metatranscriptomic taxonomic results

Experiment 11c:

Functional analysis of DE genes

Experiment 11d/e:

Al analysis of DE genes & Curation and Vetting of AI results

Environment-enriched (often ↑ in seawater/soil/hosts/particles vs LB/glucose lab)

Lab-enriched (often ↑ in rich, aerated exponential culture)

Up-Regulated in Aquatic Environments:

Down-Regulated in Aquatic Environments:

Core, conserved toolbox (works across many bacteria)

Aquatic Laboratory vs Environment Differential Gene Expression

Field-mode priorities (environment-enriched engineering levers)

Lab-biased programs (make switchable or down-tuned in field mode):

Summary: Bacillus subtilis 168 Lab biased (down tune in field)

Acinetobacter baylyi ADP1 suggested to up tune in field:

Acinetobacter baylyi ADP1 Lab biased/upregulated (suggested to down tune in field)

Environment-enriched modules

Lab-enriched modules (often down in natural waters)

Overall Summary:

Combined Species Table Laboratory vs. Environment Differential Gene Expression

References

**Corrosion Prevention Using Engineered Bacillus subtilis in Marine Environments**

**Construction of Engineered B. subtilis Strains**

**Establishing growth curves to compare growth dynamics of B. subtilis 168, 3610, and the 4 engineered 168 variants under laboratory conditions**

**Evaluating the motility of B. subtilis 168, 3610, and the 4 engineered 168 variants**

**Comparison of Acinetobacter baylyi Behavior in Laboratory vs Simulated Real-World Microcosms**

**Estimating A. baylyi survival in microcosms and control cocultures via colony counts**