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Screening and optimization of cellulase- Producing Bacteria Isolated from different Enviromental Samples using Lignocellulosis Biomass and their Utilization in Bioethanol Production
(2023) Lamsal, Usha; Jarina Joshi
This thesis investigates eco-friendly alternatives to fossil fuels in response to the demand
for sustainable energy. It focuses on bioethanol production from lignocellulosic biomass,
emphasizing the isolation, screening, and optimization of cellulase-producing bacteria.
Total 16 cellulose-degrading bacteria were isolated from garden soil, plant residues,
rotten wood, and Cow dung of Kirtipur, Chovar and Lainchour sites of Kathmandu, Nepal.
Cellulolytic bacteria were screened primarily by plate hydrolysis and further confirmed by
well diffusion method along with Congo red staining followed by NaCl treatment. Out of
12 pure bacterial isolates, 10 showed good cellulolytic activity. Notably, the cow dungderived
U1C4 isolate displayed the highest cellulolytic potential and was selected for
further studies. This isolate, identified as Bacillus cereus spp. strain U1C4 was confirmed
through morphological, biochemical, and phylogenetic analyses. Further investigations
involved utilizing various lignocellulosic substrates as carbon sources including,
Saccharum spontaneum, rice straw, wheat straw, barley straw, and wood for cellulase
production after hot water pretreatment of samples. Saccharum spontaneum showed the
highest cellulase production with cellulolytic activity 0.488 ± 0.021 IU/mL by U1C4 strain.
The crude enzyme was purified using (NH4)2 SO4
precipitation, dialysis, and
chromatography, resulting in a 5.4% recovery rate, 6.34-fold purification, and 4.693 U/mg
specific activity. The purified enzyme displayed a molecular weight of 50 kDa on SDSPAGE. Upon kinetic
analysis, the purified CMCase enzyme showed Km and Vmax values of
5.16 mg/mL and 33.22 µmol/ml/min, respectively. The optimum temperature and pH for
maximum
cellulase production were obtained as 35OC and 8 respectively including
Sacchharum spontaneum (2%) and peptone (1%) as carbon and nitrogen sources for
enhancing maximum cellulase production capabilities. Upon scaling up to a 3.5L
production medium, the optimized Bacillus sp. (U1C4) showed improved enzyme
production in an Electrolab fermenter 360 compared to a 250 mL conical flask. The
CMCase activity reached the maximum of 0.595 ± 0.021 U/mL in the fermenter on 4 th
day,
surpassing the activity of 0.484 ± 0.04 U/mL observed in the conical flask. Ethanolic
fermentation was done using a well-optimized CDBT-2 strain of S. cerevisiae after the
saccharification of S. spontaneum using U1C4 strain for 7 days and the highest ethanol
concentration, 10.73± 0.045 mg/mL was achieved on 3rd day of the fermentation process.
Additionally, the efficiency of ethanol production, as measured by the yield in relation to
the production of reducing sugars, reached an impressive 82.65%. This yield was obtained
by utilizing 17.709 mg/mL of reduced glucose during fermentation. These findings
demonstrate that ethanol can be produced from agricultural waste, highlighting the
potential of this process to generate wealth from waste.
Keywords: Bioethanol, Bacillus sp., Cellulase, Lignocellulose, Saccharum spontaneum,
Fermentation, CMCase, Pretreatment.
Labour Studies (First Semester), 2025
(Faculty of Humanities and Social Sciences, 2025) Faculty of Humanities and Social Sciences, Dean's Office, T. U., Kirtipur, Kathmandu.; .
Genomic Surveillance of Sars- Cov 2 to Reconstruct infection Dynamics and Phylodynamics using Phylogenetic Infrence of nepal
(2022) Khadka, Binod; Krishna Das Manandhar
Severe acute respiratory syndrome (SARS-CoV-2) have caused an unprecedented impact
global public health and the economy. Both current and prospective interventions require
a firm understanding of evolutionary and epidemiological parameters of novel SARS-CoV2.
Phylogenetic and phylodynamic approaches have provided critical insights into the
spread of SARS-CoV-2 in international level, aided in tracking virus genetic changes,
allowed the investigations of outbreaks and transmission chains, and informed for public
health strategy. Nepal lack any such phylodynamic study on the SARS-CoV-2 genome to
infer the epidemiological evolutionary state of virus using phylogenetic networks and
growth trends. This study aims to investigate and reconstruct the evolutionary and
epidemiological dynamics of SARS-CoV-2 virus in Nepal using the 278 genomes of SARSCoV-2
sequenced
in Biotechnology laboratory, TU. In this study, we used the Bayesian
Phylodynamic pipeline and TransPhylo to analyze and evaluate the evolutionary,
epidemiological and infection dynamics of SARS-CoV-2. Phylogenetic tree was inferred to
study the evolution of SARS-CoV-2 variants, Reproduction number of virus and
transmission chain of COVID-19 infection were estimated and the possible unsampled
cases of SARS-CoV-2 was predicted. Phylogenetic analysis showed the presence of
Omicron, Delta and Alpha variants from our dataset. Depending upon the Bayesian timescaled
phylogenetic analysis using the best fitting model showed us that the
estimated evolutionary rate of SARS-CoV-2 was 1.226×10 -3
substitutions per site per year. Estimated
reproduction number showed two growing phases, one during early 2021 and other
during early 2022. The mean estimated R value ranged from 0.495 to 4.8472. Similarly,
inference of viral transmission chain using TransPhylo showed that inferred unsampled
sources greatly outnumber the actual sequenced samples in the transmission network.
Prediction of unsampled cases using the available genome sequences also suggested that
very high cases are not being sequenced and are acting as unsampled source of infection.
Our findings highlight the critical importance of establishing genomic surveillance
programs to guarantee the current state of the epidemic and to ensure impactful decision
making for the allotment of intervention initiatives against the most relevant variants. x
Also, the study suggests the usefulness of various phylogenetic and phylodynamic
approaches in supporting the surveillance of COVID-19 and other emerging disease
outbreaks.
Keywords: SARS-CoV-2, Genomic surveillance, Phylogenetic, Phylodynamic, TransPhylo,
Bayesian Inference, Reproduction number, Transmission chain