NOTEBOOK

Wet Lab

March

  • Received 500 gm of Martian soil simulant from Prof. Sathyan Subbaiah at the Department of Mechanical Engineering, IIT Madras.


April

Week 1

Bacteria

  • Received a sample of 100 gm of calcium aluminosilicate from Astrra Chemicals, Chennai, India.
  • Purchased Pseudomonas fluorescens from the Microbial Type Culture Collection (MTCC) of the Department of Biotechnology, Government of India.


Week 2

Diatoms

  • Purchased Phaeodactylum tricornutum from the Culture Collection of Algae at the University of Göttingen.


Week 3

Bacteria

  • We received freeze dried cultures of Pseudomonas fluorescens from MTCC and revived the culture. The bacteria was grown at 30°C in a shaking incubator.
  • Glycerol stocks were made and stored at -80°C.
  • We plated the bacteria on LB plates with calcium aluminosilicate (CaAlSi) and observed the growth. However, we had difficulty dispersing CaAlSi evenly throughout the plate given its insoluble nature.

Diatoms

  • We finalized the composition of the Mann and Myers medium and the conditions required for growth and prepared the medium.
  • We received the cultures of P. tricornutum from the Culture Collection of Algae and inoculated it in the Mann and Meyers medium as 2 separate samples - static condition and shaking incubator. We observed no growth under static conditions and decided to discard it.


Week 4

Bacteria

  • We kept observing the colonies to check for solubilization zones around colonies. We could not observe solubilization zones.

Diatoms

  • We observed that the culture gets turbid but not brown, indicating unhealthy growth due to lack of photosynthetic pigments. So we decided to supplement the growth medium with vitamins: thiamine and cyanocobalamin to check if it rescues the pigment production.


May

Week 3

Diatoms

  • We suspected that the absence of biotin and inconsistencies with inoculation temperatures in our initial protocol was the reason we didn’t observe any diatom growth for several days.
  • Due to unavailability of biotin, we tried searching for alternate growth media.


Week 4

Diatoms

  • We found a paper on growth of freshwater diatoms in BG11 media that did not require biotin as an external supplement.
  • We adapted the BG11 protocol by using microfiltered seawater instead of freshwater to mimic our diatom’s natural habitat and inoculated them in a 21°C incubator with a light intensity of 410 lux.
  • Five days post inoculation, an OD of 0.14 was observed, aligning with a diatom growth study and confirming that the diatoms were thriving.


June

Week 1

Diatoms

  • We confirmed diatom growth at 27°C as well.


Week 2

Bacteria

  • Learning from our previous experiment in April, we prepared a slurry of LB and agar with CaAlSi to spread the insoluble CaAlSi evenly across the plate.
  • Despite seeing colony growth, we didn’t see a zone of clearance, hence couldn’t conclude if the bacteria were solubilizing Si.


Week 3

Bacteria

  • We found a different protocol to test the bacterial solubilization of insoluble silicates in which dextrose agar was supplemented with silicates.We implemented it.
  • No colony growth was observed.
  • In another attempt, we melted the agar after making a slurry, then let it solidify again to see if it would spread evenly. We succeeded this time in even distribution of silicates.
  • Yet again we couldn’t observe a zone of clearance and hence we had to look for better protocols.


Week 4

Bacteria

  • We found a protocol which used a defined differential media - NBRISSM. We decided to swap the magnesium trisilicate suggested by the media with calcium aluminosilicate to suit the requirements of our studies.
  • In order to make NBRISSM media as per the protocol, we prepared hydroxyapatite in our lab after consulting with experts from the Materials Science Lab at IIT Madras.
  • We inoculated P. fluorescens in our modified NBRISSM media with different BCP (indicator) concentrations and placed it in a shaking incubator at 30°C and observed every 24 hours for any color change.
  • We established an experimental protocol for inoculating P. fluorescens in the Martian soil simulant after consulting Prof. K Chandraraj, a soil microbiology expert at IIT Madras. We created a cell suspension of P. fluorescens in fresh LB and poured in martian soil simulant. The flask with inoculated soil was kept in a shaking incubator at 30°C. 1 gm of this soil was used the next day to count CFU. We noticed contamination while observing CFU.


July

Week 1

Bacteria

  • We brainstormed to refine experimental protocol for inoculating P. fluorescens in the Martian soil simulant to avoid any sources of contamination and we decided to autoclave all the materials again including spatulas used for taking out soil for CFU quantification.
  • We redid the entire experiment of soil inoculation. We took 1 gm of soil and suspended it in sterile water. This was centrifuged and the supernatant was inoculated on LB plates every 24 hours followed by counting the colonies after 14 hours incubation for the entirety of the following week.
  • We observed a color change in the silicate solubilization assay, confirming CaAlSi solubilization by bacteria.

Diatoms

  • We started with an experiment to compare diatom growth in presence and absence of silica. For that, we inoculated diatoms in 2 different media - minimal media with and without silicates and measured OD every 24 hours to compare the growth.
  • We received the plasmids pPTbsr and pPtPuc3 from Addgene as stab cultures. After propagating the culture on appropriate antibiotics we made glycerol stocks and isolated plasmids from the culture.


Week 2

Bacteria

  • After silicate solubilization was confirmed, we wanted to quantitatively estimate the amount of silica solubilized. For this we centrifuged soil after adding CaCl2 to extract soluble silicic acid.
  • We then added tartaric acid, ANSA and ammonium molybdate according to the protocol and measured the absorbance after making silica standards.
  • The results were inconsistent with the 0.2 gm/L silica standard showing more absorbance than the 0.8 gm/L silica standard.We decided to consult with a few professors about this and do some literature review on the same.
  • In the soil growth experiment, we experimented with different volumes we could take for spread plating to see what gives the best number of colonies to count and we fixed the volume at 50 μL.

Diatoms

  • We continued to measure the OD of the diatoms in presence and absence of silica.
  • We observed cell count and OD measurements every 24 hours in a separate subculture of the diatoms in order to establish a relationship between cell count and OD for the strain.
  • As the OD results were inconsistent, we continued to discuss it with professors and got back to literature reviews to figure out the reason for such small OD values.


Week 3

Bacteria

  • We continued the soil growth experiment.

Diatoms

  • We observed that diatoms initially grew similarly in silica-rich and silica-poor media, but showed significantly enhanced growth in the presence of silica in the stationary phase.


Week 4

Diatoms

  • We reinoculated the diatoms in BG11 medium.
  • The OD versus cell count calibration did not give a viable plot. We observed that this was due to variation in OD of sterile BG11 medium with time.


August

Week 1

Diatoms

  • There was no diatom growth in the reinoculated BG11 medium. We prepared the medium again and adjusted its pH to eliminate the turbidity and inoculated it.
  • We designed Gibson assembly primers for 4abh and nhoA genes for acetaminophen synthesis. We received these genes from Twist Bioscience in 2023.

Bacteria

  • Learning from the previous mistakes we made while quantifying the soluble silicic acid, we attempted the experiment again.
  • We used deionized water instead of autoclaved distilled water as the salts present in the distilled water may interfere with the experiment. Furthermore, as we were handling very small volumes, we decided to increase the volume of the reaction mixture to reduce errors. Since monomeric silicic acid is not stable, we prepared fresh standards. After making these changes, we attempted the experiment again but still got inconclusive results.


Week 2

Diatoms

  • No growth was observed in the re-inoculum. To investigate potential factors affecting growth, we substituted the seawater in BG11 medium with saltwater and prepared BG11 medium with varying saltwater concentrations - 25%, 35% and inoculated them.
  • We placed the order of Gibson assembly primers and received the order after 5 days. We created stock solutions for the primers.


Week 3

Diatoms

  • No growth was observed in any of the inoculums. Considering that the stock culture used for inoculation might be unviable, we inoculated another flask of f/2 media from the primary culture.
  • We set up a PCR reaction for amplifying the 4abh and nhoA genes. We did not receive any bands. We tried again with a higher concentration of the template DNA and received very faint bands.
  • It was reasoned that the template DNA had degraded due to non-optimal storage. To test this we performed an electrophoresis on just the template DNA and received a smear, which confirmed our suspicion.


Week 4

Diatoms

  • There was still no growth in any of the inoculum. We decided to supplement the f/2 media with a carbon source and prepared f/2 + glucose and f/2 + glycerol media supplemented with vitamins.
  • We looked at alternate ways to get new template DNA and considered using different genes.


September

Week 1

Bacteria

  • We kept looking for alternatives and decided to use the genes available in the distribution kit to engineer P. fluorescens.
  • We identified a genetic circuit and made preparations for using the kit for carrying out Golden Gate Assembly.

Diatoms

  • We inoculated f/2 + glucose, f/2 + glycerol, and BG11 media from the primary culture and incubated them at 21°C. After a few days, we shifted the cultures to a 27°C incubator.


Week 2

Bacteria

  • We transformed E. coli DH5α cells with the parts and the destination vector using heat shock and inoculated them on the appropriate antibiotic plates.
  • We grew the transformed colonies and isolated the plasmids from them. Plasmid concentration was measured using a Nanodrop spectrophotometer.
  • We prepared P. fluorescens competent cells.

Diatoms

  • Growth was observed in BG11 and f/2 + glycerol media. We reinoculated fresh media with samples from both of them.


Week 3

Bacteria

  • We finalized the protocol to be used for Golden Gate Assembly and procured the enzymes for it. We set up a 10 μl reaction and incubated in a thermocycler following the protocol. Following this, we transformed the assembly product into E. coli DH5α cells.
  • Next day, we received several colonies, some of which were fluorescent (colonies with self-ligated vectors). We picked the non-fluorescing colonies and isolated our assembled plasmids.
  • We decided to confirm the assembly success through restriction digestion. On running the electrophoresis, we observed the bands as expected.
  • We decided to transform electrocompetent P. fluorescens cells with our assembled plasmids.

Co-Culture

  • In order to determine the salinity range of the co-culture medium for optimal bacterial growth, we prepared a setup involving soil inoculated with bacterial culture and minimal media with varying seawater concentrations.


Week 4

Bacteria

  • After transforming P. fluorescens, we observed 6 colonies on one of the test plates, however there were 2 colonies on the negative control plate.
  • To rule out faulty preparation of antibiotic plates, we made a new kanamycin plate. We picked the colonies and streaked on the new kanamycin plate.
  • All the colonies from the negative control plate grew on the new plate. This prompted us to attribute the colony formation to contamination.
  • We tried transformation again with new cuvette tubes and increased our precautionary measures. We received one colony on a transformant plate and no colonies on the control plate.
  • We picked the colony and propagated it for further analysis.

Co-Culture

  • We observed good bacterial growth in all 4 salinities: 30%, 15%, 7.5% and 5%. We proceeded to set up a co-culture using minimal water in 100% seawater since it has the optimal salinity value for diatom growth.
  • We quantified growth of bacteria and diatoms in the co-culture setup by measuring the OD and compared it with growth of bacteria and diatoms in separate cultures. We found that both organisms were growing better in co-culture.

Model

March

  • GSMM Integration: Successfully loaded the genome scale metabolic model of the diatom into COBRApy, enabling computational metabolic modeling.
  • Literature Review and Flux Balance Analysis (FBA): Conducted a comprehensive review of biochemical pathways and reaction mechanisms, followed by basic FBA to evaluate the organism's growth and metabolic flux distribution.
  • GSMM Modification: We investigated strategies for incorporating the new genes 4abh and nhoA, and the newly synthesized metabolites 4-aminophenol and acetaminophen, into the genome scale metabolic model to expand its functional capabilities.
  • FBA Validation: Performed FBA to assess changes in flux distributions and metabolic efficiency post-introduction of the acetaminophen synthesis reactions.


April

  • Literature Review: Started literature review on adding side reactions to the GSMM.
  • BLAST Search and Enzyme Identification: To incorporate the side reactions, we identified candidate enzymes in the diatom via Protein BLAST. Based on this, we added 4 side reactions to the model.
  • Reaction Addition and Flux Issues: Incorporated a secretion reaction for acetaminophen, but encountered issues generating the correct flux. Added all the exchange and demand reactions correctly and showed the flow of metabolites.


May

  • Model Stabilization and Feedback: Fixed side reactions and achieved stable steady-state flux. Met with Dr. Karthik Raman, our PI and an expert in computational systems biology, for insights into the next steps. Through this, we identified an issue with the biomass reaction.
  • Model Replication and Comparison: We integrated the acetaminophen synthesis reactions into an E. coli model to compare with the fluxes we were getting in the diatom.
  • Basic Dynamic Model Development: Started working on the dynamic model for silica solubilization and built a basic network model of the silica solubilizing bacteria using SimBiology.


June

  • GSMM Analysis: For the GSMM we integrated multiple analysis tools, including PFBA, MOMA, ROOM, FVA, GFBA, analysis of growth medium, gene knockouts, FSEOF, and MetQuest.
  • Escher: Identified a problem where the metabolic network plotting software Escher only displayed the E. coli model for any input GSMM. Explored a solution involving manual addition of reactions.
  • Parameter Optimization: Determined rate parameters for the silica solubilization model.
  • Community Modeling: Started looking into MICOM and its potential to understand how the co-culture of bacteria and diatoms would behave.


July

  • GSMM Refinement: Discovered a missing NH₃ exchange reaction in the existing GSMM and worked on addressing this gap. The addition of the reaction changed the fluxes quite a bit, proving that ammonia is an important metabolite in the diatom’s pathways.
  • Flux Analysis: Worked on various plots to optimize biomass and acetaminophen production. Analyzed reactions using PFBA, MOMA, and ROOM approaches to generate comparative flux plots.
  • Escher: Attempted to map key pathways involving amino acids biosynthesis (chorismate) using KEGG and Escher. Faced issues with visual clarity due to map complexity.
  • Silica Solubilization Dynamic Modeling: Conducted a detailed analysis of silica solubilization. Documented internal and external metabolite concentrations. Examined pH variation over time at different intervals (Hour 1, Hour 10, Hour 60). Investigated how these parameters interact within the reaction network.
  • MICOM Tool Discussion: Approached Dr. Maziya Ibrahim in the Computational Systems Biology Lab, IITM, to discuss MICOM for co-culture network modeling. Key points included adjusting growth medium bounds, cooperative tradeoff, flux generation, and optimization steps. Started modifications to GSMMs based on these insights.


August

  • Limonene Production: We modeled the production of limonene in Pseudomonas using constraint-based modeling and its associated analysis tools.
  • MICOM: Completed modeling workflows and generated plots.


September

  • Biological Interpretation of Modeling Results: Made key inferences from the models to improve growth and product yields.

Software

April

  • Discussed potential problem statements for a software with applications in space synthetic biology.
  • Identified, based on our experience coming up with our wet lab project, that chassis selection is difficult for achieving in situ resource utilization.
  • We decided to try and map functional groups present in compounds to enzymes, so that if we had a list of enzymes present in an organism, we could identify which compounds would react with these enzymes and be a part of the metabolism of the organism.
  • Decided to use SMARTS and SMILES notation as possible methods of input for functional groups to our program.
  • Explored RDkit , an open-source toolkit for cheminformatics, to try to convert between various formats of input.
  • Implemented the RDkit library in Python to parse molecules in SMARTS and SMILES notations.


May

  • Conducted review of the EC number notation.
  • For each sub-subclass, we tried to write the corresponding functional group in SMARTS notation.
  • Decided to abandon this method, as there were too many functional groups to compile manually. Each sub-subclass had multiple functional groups under it, and they would each react with different metabolites.
  • Ideated on other methods of obtaining a list of chassis.
  • Explored various databases such as BioCyc, MetaCyc, RCSB PDB, Uniprot and KEGG.
  • Manually conducted literature review of papers concerning biomining and bioleaching, to identify useful reactions that might not be present in the databases.
  • Realized the need for rational scoring of chassis and ideated on structure of scoring function.


June

  • Continued to conduct literature review, and also try to find various other databases we could use for metabolite searches, such as omnicrobe.
  • Literature review for physiological conditions preferred by organisms was conducted, to no avail.
  • Tried to create a workflow to find the organism through a compound in BioCyc. Ran into issues, as BioCyc is not a database for organisms, and only lists organisms as possessing a pathway if there has been extensive documentation and research performed.
  • KEGG tested different pathways, found compound → enzyme → gene → organism to be best.
  • Performed literature review to arrive at parameters for scoring function.
  • Tried to get a list of species from the identified pathway from the BioCyc website.
  • Looked into a github module that integrates BioCyc’s functionality into Python.
  • Improved preprocessing, implemented batching requests in KEGG, approx 2 min per compounds search.
  • Explored implementation of resourcefulness and survivability parameters, arrived at score for temperature and pH.


July

  • Installed the BioCyc GitHub module in Python and tested it out.
  • Tried to construct a rough workflow to find the list of organisms from an input in BioCyc.
  • Looked into using BRENDA to complement KEGG results at enzyme stage.
  • Set up local lookup table, implemented multiprocessing in KEGG, approx 30s-1min per compound search.
  • Explored implementation of engineeribility parameter, found it hard to define and implement.
  • Looked into possible inputs we could provide to the BioCyc code. BioCyc ID was the one compatible with the github library, but it eliminated the input of synonyms as entries.
  • Looked into how ‘Reactions’ and ‘Pathways’ were defined, and what characteristics they had as outputs by using the github library for BioCyc.
  • Tried to set up BRENDA SOAP API (and failed).
  • Switched to CSV download functionality on BRENDA instead of messing about with SOAP API.
  • Started Django implementation of input forms for the web tool of Astrolabe.


August

  • Implemented code to get a list of reactions from a given BioCyc ID. Also implemented code to get a list of pathways from the list of reactions.
  • Integrated BRENDA and KEGG code for more comprehensive searches.
  • Ideation on extracting culture media details from BacDive.
  • Finished input functional version of the Django-based web tool.
  • Tried to implement the library ourselves by using the requests library and directly using BioCyc URLs. There were issues due to the BioCyc database being accessible when on a paid account, so we uploaded our credentials as a requests session.
  • Noticed numerous references to MediaDive via BacDive, so set up MediaDive API.
  • Figured out pathways to integrate MediaDive to get culture details.
  • Implemented design aesthetics in the Django web tool for Astrolabe.


September

  • Continued to implement by directly using URLs from BioCyc.
  • Implemented a section of code to convert ChEBI IDs to BioCyc IDs for uniform inputs.
  • Set up MediaDive code to obtain medium composition and pH.
  • Integrated BacDive and MediaDive code to get culture info from MediaDive when referenced in BacDive.
  • Implemented scoring function to score organism results from each database individually.
  • Integrated with scoring function and other API’s to complete the software integration for the Astrolabe web tool.
  • Finished implementing the BioCyc code. Started writing content for the wiki.
  • Implemented a function to remove those organisms belonging to ‘Metazoa’ and ‘Embryophyta’, to eliminate multicellular organisms from the kingdoms Plantae and Animalia in the BioCyc code.
  • Modularized BacDive and MediaDive code, split everything into files and set up proper libraries and pathways.
  • Integrated all databases to parallelly generate organism lists to be passed to the scoring function.
  • Purchased remote server for Astrolabe web tool hosting via a free duckdns domain. Configured the server and hosted the tool on the internet.