Studies using DOSE

[1] Castillo, CFG, Ling, MHT. 2014. Digital Organism Simulation Environment (DOSE): A Library for Ecologically-Based In Silico Experimental Evolution. Advances in Computer Science: an International Journal 3(1): 44-50. [Abstract] [PDF]

Two experiments (see Case Studies 1 and 2 in Examples and Case Studies) to examine the effects of migration on heterozygosity (local genetic distance) given that mating is only allowed within their own ecological cell. Our simulation results showed that adjacent migration, such as foraging or nomadic behaviour, increases heterozygosity while long distance migration, such as flight covering the entire ecosystem, does not increase heterozygosity.

[2] Castillo, CFG, Ling, MHT. 2014. Resistant Traits in Digital Organisms Do Not Revert Preselection Status despite Extended Deselection: Implications to Microbial Antibiotics Resistance. BioMed Research International 2014, Article ID 648389. [Full Text] [PDF]

We examined whether antibiotics resistance will decline after disuse of specific antibiotics under the assumption that there is no fitness cost for maintaining resistance. Our results show that during disuse of the specific antibiotics, a large initial loss and prolonged stabilization of resistance are observed but resistance is not lost to the stage of pre-resistance emergence. This suggests that a pool of partial resistant organisms persist long after withdrawal of selective pressure at a relatively constant proportion. Subsequent re-introduction of the same antibiotics results in rapid re-gain of resistance. Thus, our simulation results suggest that complete elimination of specific antibiotics resistance is unlikely after the disuse of antibiotics, once a resistant pool of micro-organism has been established.

[3] Castillo, CFG, Chay ZE, Ling, MHT. 2015. Resistance Maintained in Digital Organisms Despite Guanine/Cytosine-Based Fitness Cost and Extended De-Selection: Implications to Microbial Antibiotics Resistance. MOJ Proteomics & Bioinformatics 2(2): 00039. [PDF]

Continuing from our previous work (Castillo and Ling, 2014), we added a GC-based fitness cost for maintaining resistance. In essence, antibiotic resistance traits are defined consecutive '0' in a binary chromosome and the ancestral chromosome is 50 repeats of '1010101010'. If we take '0' to represent 'G' or 'C' and '1' to represent 'A' or 'T', the ancestral chromosome will have 50% GC content and the antibiotic resistance traits will reduce the GC-content; hence, incurring a fitness cost as GC content is an important genetic feature in the biological world. Our results showed similar trends in resistance compared to our previous work on no fitness cost (Castillo and Ling, 2014), at all stages of initial selection, repeated de-selection and re-introduction of selective pressure. This suggests that complete elimination of specific antibiotics resistance is unlikely after the disuse of antibiotics despite presence of fitness cost in maintaining antibiotic resistance during the disuse of antibiotics, once a resistant pool of micro-organism has been established.

[4] Kwek, BZN, Ardhanari-Shanmugam, KD, Woo, JH, Usman, S, Chua, JW, B, V, Shahrukh, K, Thong-Ek, C, Ling, MHT. 2019. Random Sequences May Have Putative Beta-Lactamase Properties. Acta Scientific Medical Sciences 3(7): 113-117. [PDF]

Beta-lactamases, which confer resistance to beta-lactam antibiotics, is of medical and healthcare concerns globally. Studies had placed the emergence of beta-lactamases to more than 2 billion years ago. However, it is not known where the first beta-lactamase originate. In this study, we examine the probability of de novo emergence of putative beta-lactamase from random sequences. A set of 10 thousand randomly generated sequences were aligned using Smith-Waterman algorithm and Needleman-Wunsch algorithm to a set of known class D beta-lactamases isolated from GenBank to determine the probability of each randomly generated sequence as putative beta-lactamases. Our results suggest that substantial proportion of randomly generated sequences may be putative beta-lactamases, with 4% of the randomly generated sequences showing 99% probability as putative beta-lactamases. To test whether a putative beta-lactamase can evolve over generations to have more characteristics of known beta-lactamases, in silico evolution was carried out using DOSE, an evolution simulation software. Our simulation results also suggest that a putative beta-lactamase may rapidly evolve into a more functional beta-lactamase under selection. Hence, de novo origination of beta-lactamase from random sequences is plausible.

[5] Ardhanari-Shanmugam, KD, Shahrukh, K, B, V, Woo, JH, Thong-Ek, C, Usman, S, Kwek, BZN, Chua, JW, Ling, MHT. 2019. De Novo Origination of Bacillus subtilis 168 Promoters from Random Sequences. Acta Scientific Microbiology 2(11): 07-10. [PDF].

How the first promoters may have originated is of evolutionary curiosity. Several studies have shown that new promoters arise by copying over an existing promoter sequence. Although de novo origination of promoters has also been suggested, there has been limited evidence. Hence, we investigate the possibility of de novo origination of promoters in this study using the model organism Bacillus subtilis 168. 10,000 random sequences were generated and alignment to known promoter sequences from B. subtilis 168 were used to assess their probability of being putative promoters. Results showed that 380 out of 10,000 random sequences have ≥97% probability. In silico evolution was performed to test the possibility of promoter selection using selective pressure and our simulation results suggest that the functionality of a random sequence may increase overtime. Therefore, de novo origination of promoters from random sequences is possible.

[6] Usman, S, Chua, JW, Ardhanari-Shanmugam, KD, Thong-Ek C, B, V, Shahrukh, K, Woo, JH, Kwek, BZN, Ling, MHT. 2019. Pseudomonas balearica DSM 6083T promoters can potentially originate from random sequences. MOJ Proteomics & Bioinformatics 8(2): 66‒70. [PDF].

Recent studies and researches have proposed that many genes are plausibly emerged from previously non-coding genomic regions. However, how a promoter can emerge and function properly from de novo genes remain debatable as this has not been show in large numbers of organisms. Therefore, this study aims to explore the possibility of de novo evolution of a promoter from random sequences by using Pseudomonas balearica DSM 6083T as the model organism. Our result shows that 39.3% of the generated random sequences have 68.6% probability to be a functional promoter. Evolution simulation was carried out to observe the effect of evolution in the putative P. balearica promoter over generations. The simulation result proves that selection enhances the functionality of the generated random sequences overtime. Therefore, it is plausible that P. balearica promoter could emerge from random sequences, which is consistent with findings from previous studies.