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Months | Work Done |
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January |
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February |
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March |
*Due to CoVID-19, all the team activities came to a halt and plans were suspended Attended Ambassador Calls to share the challenges faced by the team and seek guidance |
April |
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May |
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June |
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COVID impacted our project journey and roadmap significantly, as accessing funding, labs, experiments and Team Work became difficult to realise. Settling in the new format took us some time and by June 15 we had finalised the core team members. With brief plans to proceed in 5 main directions - Research Design, Software, Human Practices, Public Engagement, and Machine Learning, we formalised our subsystems and worked on the team constitution. The iGEM IIT Roorkee Constitution was drafted to lay down the team structure and guidelines for future teams from IIT Roorkee. We maintained a new lab notebook to track our progress and fulfillment of project goals in different categories.
Wet Lab
- Researched on microbiomes and thought of possible application of Pyocin in gut microbiome research
- Worked on design of alternate pyocins with tail fibers of other A. baumannii phages
- Considered the possibility to use iron in the formulation which prevents Ab infection
- Researched Urinary tract infection and wound infections as a possible target
Dry Lab
- Chartered pipeline for gene detection
- Coded for multiple sequences alignment.
- Computed a gene detection algorithm using python which works as the first process of the TailScout
- Read papers in machine learning for protein-protein interaction
Human Practices
- Applied for Official iGEM Mentor
- Mentorship meeting with IISER Bhopal to understand project planning
- Attended German iGEM Meetup
- Interviewed Dr. Anand Ratan Tiwari
- Worked out on the Webinar Brochure and mails
- Initiated AMR awareness campaign for the college students
Wet Lab
- Engineered plasmid using gibson assembly
- Faced issues with sequence complexities that required expert opinion and guidance
- Decided to target pneumonia under all possible Ab infections
- Devised the possibility of aerosol based delivery of our drugs directly to the site if infection
- Researched and conceptualised inhaled protein therapeutics
Dry Lab
- Debugged errors in the gene detection algorithm and saw research about Biopython library
- Scouted deep models in Machine learning
- Identified the possibility for including games on AMR in the wiki
Human Practices
- Compiled the School database for the Webinar
- Outlined the Presentation for School Webinars
- Rolled out mails to school
- Formulated the resource booklets (according to different learning standards)
- Collaboration meeting with team iGEM Montpellier
Wet Lab
- Opted for DNA Synthesis instead of cloning
- Plasmid sent for verification
- Validated gene fragments
- Communicated with IDT Customer service for optimizing sequences for synthesis
Dry Lab
- Orchestrated the software development workflow
- Catalogued various machine learning based approaches in AMR
- Formulated modelling methodologies for the fusion protein
- Decided on bioinformatics modeling due to lack of lab access in COVID
Human Practices
- Hosted a webinar in St. Anne's Convent School, Chandigarh.
- Collaborated with National Service Scheme IIT Roorkee
- Hosted a webinar in ‘Srijan - Ek Soch’ NGO
- Interviewed Dr. NandKishore Joshi
- Released AMR Mythbusters and Team Introduction on social media handles
Wet Lab
- Read papers on HAI’s and Ventilator-Associated Pneumonia caused mainly by A. baumannii
Dry Lab
- Prepared the phage tail fibers database of their protein sequence. I.e, phage library
- Started with structural modeling, energy minimization, and docking studies for proof of concept
Human Practices
- Hosted a Webinar at Delhi Public School, Ghaziabad Vasundhara
- Stimulated All India iGEM Meet 2020
- Formulated content for ML workshop in All India iGEM Meet
Wet Lab
- Studied VAP for Proposed Implementation
- Meeting with Dr. Kulkarni helped set the points and made us focus on VAP.
Dry Lab
- Searched for the Clustal Omega MSA and Jpred Secondary Structure Prediction REST Api’s
- Decided to try all the three modeling methods and compare results
Human Practices
- Fabricated our Presentation and Poster for AIIM
- Consulted Dr. Rajesh Kulkarni to understand VAP infections
- Conducted All India iGEM Meet
Wet Lab
- Conducted in depth research and analysis Ventilator Associated Pneumonia
- Designed the delivery system based on nebuliser based-therapeutics
Dry Lab
- Read papers for using Clustal Omega on the web server-based application
- Founded error in first run for the models due to large size of model protein
Human Practices
- Initiated collaboration activities for other iGEM teams
- Project discussion with IISER Tirupati
- Created Team Spirit Poster for Global iGEM Meetup
Wet Lab
- Switched from nebuliser system to Bolus delivery system
Dry Lab
- Tested the individual codes on the system with different phages fibres
- DId literature review for the model and found out that N-truncated fragment was sufficient for modeling
Human Practices
- Prepared and rolled out emails to stakeholders (Clemedi, APT)
- Attended Global iGEM Meet
Wet Lab
- Worked on Final Plasmid assembly with the help of Twist Biosciences
Dry Lab
- ML approach discussions with Keerat and Harkirat
- Added a more bacteriophages in the library
- Identified the fusion protein sequence by crossing over AP22 bacteriophage with R2-NTF pyocin tail fiber instead of the complete R2 pyocin tail fiber
Human Practices
- First phase meeting with Clemedi
- Proctored patient Interview
- Received inputs from the iGEM judging committee that guided our further work
Wet Lab
Dry Lab
- Preliminary ML Analysis
- Made Github repo for the WebServer and committed initial codes
- Constructed the new sequence for the fusion protein - for 3 modeling methods
Human Practices
- Second Phase meeting with Clemedi
- Finalised our Team Merchandise
Wet Lab
- Worked on safety forms
Dry Lab
- Tried to integrate the python code and REST Api’s but failed
- Once the models were built, identified parameters that would help in comparing these models
- Decided to compare alignment RMSD values for alignment with R2-NTF pyocin and AP22 phage
Human Practices
- Dispatched Learning material to Anushruti Academy for the Deaf via NSS
- Participated in the survey Collaboration by IISER Berhampur and CCU iGEM
Wet Lab
- Submitted Safety forms
Dry Lab
- Discussion with Mentor to finalize ML approach
- For the next iteration for integration, learnt through videos on youtube of Django
- Meetings with Institute Seniors for software integration
Human Practices
- Project Discussion Meeting with Mentor
- Designed survey for gauging the problem of HAI through medical staff
- Conducted Medical Staff Survey
Wet Lab
Dry Lab
- Discussion with institute administration for providing high computing PC
- Made a presentation for running all the codes locally on an individual system
- Decided to compare the Ramachandran plots of the models as well
Human Practices
- Built storyline script with Subtitles for Project promotion video
Wet Lab
Dry Lab
- Collection of the dataset for ML
- Meeting with the mentor for discussion on the integration part and sent out a document explaining our problems and issues to relevant contacts
- Discarded all the models obtained via threading from consideration because of their monomeric structure
Human Practices
- Organised Awareness Quiz in AAD in collaboration with NSS
- Wrapped up the production of Project Promotional Video
Wet Lab
Dry Lab
- Preprocessed the dataset collected
- Django integration completely (i.e. Backend)
- Set weightages for the comparison parameters andgave Ramachandran plot data the highest weightage
Human Practices
- Collaborated with AUC Egypt - “Thank You Mentor”
- Launched our Project Logo on Social Media platforms
Wet Lab
Dry Lab
- Machine learning experiments completed
- Carried out energy minimization for the best chosen model using Yasara energy minimisation toolkit
Human Practices
- SDG Collaboration with iGEM UPCH Peru
- Participated in the Collaboration “Envirospeaks” by iGEM RUM
Wet Lab
- Developed Protocols
- Collected the data of preliminary experiments for the wiki
Dry Lab
- Working on the deployment of the web server
- Studied protein-protein interaction through docking
- Searched the structure of the LPS receptor and the fusion protein but it wasn’t available in existing databases so, couldn’t perform docking
Human Practices
- Co-produced Policy Review Report on AMR (with NSS IITR)
- Ideation on hosting webinars in collaboration with NSS for underprivileged students of Roorkee schools
Wet Lab
Dry Lab
- Collected available results of all the modeling
- Sorted the Machine learning experiment results
Human Practices
- Finalised all collaborations
- Started our iGEM⤬SDG Collaboration - “SMILE”