Genesis of Antibiotic Resistance AR XLIII “Migration Ratio” ( M ) Dependent Alteration of AR Gene (ARG) Pool Augment Antibiotic Resistance Pandemic (ARP): A Retrospective Appraisal

Here we present the impact of migratory pattern on the AR. Our model for this investigation is MC‐TDSHSR8. This location for this study based on the following factors:Rate of border crossing by the residents of Mexico ‐ United States. Factors such as, the proportion of migrant individuals to the total number (before and after migration) of individuals in the population referred as migration ratio (M); the difference between the allelic (gene) frequencies ( af ) of the migrant individuals and that of the resident population into which migration has occurred are contributing factors altering the af . Migration ratio ( m ) in MC‐TDSHSR8 for 2016 is estimated as follows: m=M / (N+M) where M is the number of migrant individuals, and N is the number of individuals in population before migration. Maverick County population estimates, as of July 1, 2017, 58,216 while Foreign born persons, represent 33.1% and a variable number for migrants per annum. Thus, the Migration ratio ( m ): M=9,975; N=58,216; Solving for m = 9975 / 58,216+9975 = 0.146. If the frequency of allele a in the population before migration is Q 0 (58,261) ; migrant individuals = Q m (9975) ; migration ratio = m(0.146); frequency after the migration = Q 1 , weighted average of the two frequencies Q 0 and Q m (58216+9975)/2=34095.5; then Q 1 = Q 0 (1−m) +m Q m . Thus, the amount of change in the value of q. represented by Q , due to migration in one generation will be: Dq = m ( Q m − Q 0 ) ; solving for Dq = 0.146 (9975–58216)= −7043. If the migration from a given population was recurrent, the rate of migration was the same in each generation (the migration ratio, m , had the same value), and migration occurred for n generation, would be:Dq = Q n − Q m =(1−m) n ( Q o − Q m ) or (1−m) n =( Q n − Q m ) / ( Q 0 − Q m ), where Q n is the value of Q after n generations of constant recurrent migration from the same population, n is the number of generations for which migration has taken place. However, the data on migrant workers were variable due to multitude of contributing factors dependent on the socioeconomic cultural family criteria. Given the incertitude of data on migrant workers, determining the Dq for gene frequency after given number of generation would be considered as erroneous. However, the trend on the impact of the migration ratio ( m ) as an evolutionary force or evolutionary factors in the alteration of ARG frequencies were solved as per Wright‐Fisher Model (WFM)– Migration represented as r +1: z ( r +1)| z( r ) ~Bin(2N, (1− m ) x ( r ) + m x c . Addressing the multitude of evolutionary pressure on af of ARG, as a function of g:[0,1] → [0,1], implying the alteration of sampling probability of binomial distribution presented in Equation: z ( r +1)| z( r ) ~Bin(2N, x ( r )) yielding z ( r +1)| z( r ) ~Bin(2N, g ( x ( r )) implies that evolutionary pressures such as genetic drift, mutation and migration are linear in x, referred as General Linear Evolutionary Pressure Model . Support or Funding Information Supported by Professional Development Funds to Subburaj Kannan This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .