Prevalence, associated factors and antimicrobial susceptibility patterns ofSalmonellaspecies and pathogenicEscherichia coliisolated from broiler poultry farms in Wakiso district, Uganda

(F) TGG GTG CAC GAG TGG GTT ACblaTEM (R) TTA TCC GCC TCC ATC CAG TC 526 58 Tenover et al., 1994 204 205 The PCR master Mix reagents was prepared as follows: 206  12.5 µL master mix consisting of One Taq quick load two times master mix/w standard 207 buffer, 208  dNTPs&Taq polymerase (M0486S), 209  1.5 µL forward (100 µM), 210  1.5 µL primary reverse (one hundred µM), 211  5 µL DNA template and RNAse-free dH2O up to 25 µL. 212 PCR Cycling: The PCR process was carried out in a thermo cycler (Perkin Elmer, 213 Wellesley, MA, USA) with a pre-denaturation cycle of 95°C for 15 min, followed by DNA 214 amplification stage with 30 cycles (94°C for 1 min, 58°C for 1 min, and 72°C for 1 min) 215 and final extension cycle of 72°C for 5 min. 216 DNA Amplicons were electrophoresed using 1.5% agarose gel, in Tris-Borate EDTA 217 buffer (TBE) 1×concentration, Safe View ClassicTM DNA stain, 6x loading dye (Thermo . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 218 Scientific), and DNA ladder/marker 100 bp (Sigma-Aldrich, Inc., Saint Louis, MI, 219 USA)DNA Bands were visualized on a Dark reader Transilluminator. 220 221 Data Management and Analysis 222 223 All records of the analysis were recorded in the lab register as a hard copy back up. 224 Samples were assigned codes and excel spreadsheets were used to enter the raw data, 225 which were then exported to Stata (Version 12, Special Edition, College Station, Texas 226 USA) software for statistical analysis. Frequency tables, graphs were used to present 227 descriptive statistics. This was done at a univariate analysis level. 228 Bivariate and multivariate analyses was carried out for the study objectives, quantitative 229 data evaluations was made in relation to the 95% level of significance/confidence, the 230 Pearson value (p-value ) to determine the objective variables' statistical significance, 231 statistics were judged to be significant for any p < 0.05. 232 233 Ethical Consideration 234 Approval was obtained from Mbarara University of Science and Technology ;Institutional 235 Ethical Review Committee (MUST-2021-141), and at the ministry level, permanent 236 secretary Ministry of Agriculture, Animal Industries, and Fisheries, district's chief 237 administrative officer, and district veterinarian. 238 Prior engaging the farms, the researcher sought for clearance from the farm owners to 239 access and collect samples from their farms. This consent was requested voluntarily to 240 participate in the study. The researcher treated all Farm's data and bacterial isolates 241 obtained for this investigation in strict confidence. 242 243 COVID19 Prevention and Management Plan 244 245 The researcher received the recommended two doses of COVID-19 vaccination. In addition 246 to this, the researcher adhered to the government recommended standard operating 247 procedures such as avoiding touching surfaces at the poultry farms on any place while 248 carrying out this study, frequent washing/cleaning of the hands with soap or sanitizers, strict 249 face masking while carrying out this study and the respondents will also be encouraged to 250 put on their face masks. Social distancing was also adhered while interacting with persons 251 at the time of data collection. . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 252 253 Quality assurance and Quality control procedure: 254 255 Involved the use of reference controls (both positive and negative). During the data entry 256 and analysis, the researcher ensured double entry of data to rule out clerical errors. 257 RESULTS 258 Prevalence of Salmonella and E. coli from the cultured samples: 259 260 Of the total of 216 samples collected, a total of 40 (18.5%) Salmonella and 120 261 (55.6%) Pathogenic E. coli was isolated as seen in the flow chart (figure 2). 262 263 Demographic and socio-economic characteristics of the respondents 264 265 Out of 216 farm managers selected from ten (10) different sub counties in Wakiso district 266 that took part in the research and were interviewed, 87 (40.28%) were Males and 129 267 (59.72%) were females. The age group of31-45years had the most participants at 268 113 (52.31%) while the age group of 46 and older had the fewest 50 (23.15%). In regards 269 Education level training; at least all the farm managers had some basic training. 270 Participants who completed primary level were 58 (26.85%), Secondary level were 80 271 (37.04%), vocational training were 33 (15.28%) and University level were 45 (20.83%). 272 When examining the various farm managers' sources of income, the survey discovered 273 that 146 participants (67.59%) relied primarily on poultry, others had mixed agricultural 274 practices like livestock farming (including either cattle, Sheep, Goats or Piggery) alongside 275 poultry 22 ( 10.18%), crop farming with poultry 17 (5.56%) and others had 276 additional funds arising from self-employment in other sectors alongside the 277 poultry 31 (14.35%) as seen in table 3. 278 279 Table 3: Farm characteristics and demographics: Characteristics Percentage (Variable) Category Frequency (N=216) (%) Male 87 40.28Gender Female 129 59.72 15-30 53 24.54 31-45 113 52.31 Age(years) >=46 50 23.15 Primary 58 26.85Education level Secondary 80 37.04 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint Vocational Training 33 15.28 University 45 20.83 Kitabi 25 11.57 Namugongo 28 12.96 Kiira 32 14.81 Makindye 28 12.96 Nabweru 19 8.79 Kakiri 21 9.72 Busukuma 11 5.09 Wakiso TC 16 7.40 Masulita 12 5.55 Sub counties Nsangi 24 11.11 Poultry alone 146 67.59 Livestock farming (Cattle, goats, sheep, or Pigs) with poultry 22 10.18 Crop farming with Poultry 17 5.56 Source of income Self-employed off-farm. (Others) 31 14.35 Once per Month 13 6.02 Once per week 117 54.17 hygiene/rate of cleaning of the farm Daily 86 39.81 Other Birds (Ducks, Turkey, and Geese) 68 31.48Presence of other animals (Pigs, Cows, Ducks and Turkey) Livestock 148 68.52 Deep Liter 103 47.69 Battery Cage system 82 37.96 mixed farming with turkey and ducks 19 8.76 Type of production system used Semi intensive (Free range system) 12 5.56 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 11 281 Factors associated with Salmonella and Pathogenic E. coli in broiler poultry farms 282 in Wakiso District. 283 284 Salmonella and pathogenic E. coli were most frequently found in broiler poultry farms where 285 there was contact between poultry and other bird species like turkeys and geese (P-value= 286 0.019), contamination of commercial poultry feeds (P-value=0.012), movement of farm 287 workers between pens (P-value=0.167)and use of untreated water (P-value=0.117). 288 Therefore, there is a significant association between the above variables and the presence 289 of the organisms of interest in the research (table 4). 290 291 Table 4: Showing factors associated with Salmonella and E. coli in poultry 292 farms in Wakiso District 293 Salmonella E. coli Variable Category Frequency (n)=40 P-value Frequency (n)=120 P-value Livestock 83 (69.2) 65 (81.25%) Contact of poultry and other bird species Other birds 25 (20.8) 0.384 15 (18.75%) 0.020 Daily 96 (80) 49 (61) Once a week 21 (17) 26 (33) Frequency of cleaning and disinfection of the Bird's Housing. Once a Month 03 (3) 0.498 05 (6) 0.113 Mixed with Water 95 (79.2 56 (70)contamination of commercial poultry Mixed with other

25 (20.8) 0.242 24 (30) 0.002 From one pen 58 (48.3) 55 (68.75%) movement from one pen to the other by farm- handlers From more than one pen 62 (51.7) 0.244 25 (31.25%) 0.017 Use of well water 38 (31.7) 32 (40)use of untreated water Use of tap water 82 (68.3) 0.392 48 (60) 0.018 Home made 46 (38.3) 25 (31)Source of poultry feeds Commercial 74 (61.7) 0.066 55 (69) 0.237 294 295 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 12 296 297 Antibiotic susceptibility patterns of Salmonella and Pathogenic E. coli towards 298 commonly used antimicrobials in poultry: 299 300 The phenotypic resistance profile for Salmonella organisms from broiler poultry samples 301 when subjected to the selected antibiotics demonstrates that ampicillin 32 (80%) is the drug 302 with the highest level of resistance, followed by erythromycin 28 (70%), tetracycline 27 303 (67.5%), and ciprofloxacin 25 (62.5%). On the contrary, low resistance was observed to 304 ceftazidime 10 (15%), Gentamicin 3 (8%), Chloramphenicol 3 (8%), cefepime 2 (5%) and 305 meropenem2 (5.0%) as shown in table 5. 306 307 Table 5: showing antibiotic susceptibility patterns of Salmonella towards commonly 308 used antimicrobials in Poultry: Antibiotics Resistant n (%) Intermediate Resistance n (%) Susceptible n (%) Gentamicin (GM) (10 μg/ml) 3 (7.5) 7 (17.5) 30 (75.0) Meropenem (MEM) (10 μg/ml) 1 (2.5) 2 (5.0) 37 (92.5) Ceftriaxone (CRO) (30 μg/ml) 18(45) 4 (10) 18 (45) Chloramphenicol (CHL) (30 μg/ml) 3 (7.5) 3 (7.5) 34 (85) Cefepime (CPM) (30 μg/ml) 2 (5.0) 3 (7.5) 35 (87.5) Ciprofloxacin (CIP) (5 μg/ml) 25 (62.5) 10 (25) 5 (12.0%) Erythromycin (EM) (30 μg/ml) 28 (70) 7 (17.5) 5 (12.5) Ampicillin (AMP) (10 μg/ml) 32 (80) 2 (5) 6 (15) Tetracycline (OXT) (30 μg/ml) 27 (67.5) 6 (15) 7 (17.5) Sulfamethoxazole-trimethoprim (SXT) (25 μg/ml) 20 (50) 5 (12.5) 15 (37.5) Cefotaxime (CTX)(30µg/ml) 10 (25) 2 (5) 28(70) Ceftazidime (CTZ) (30µg/ml) 15 (37.5) 5 (12.5) 20 (50) 309 310 E. coli exhibited the highest resistance to Erythromycin at 88 (73%), followed by Ampicillin 311 86 (72%), Chloramphenicol 85 (71%), Tetracycline at 82 (68%) and sulfamethoxazole- 312 trimethoprim at 78 (65%). However, it’s worth noting that there was observed very low 313 resistance to Ciprofloxacin 9 (8%), meropenem 4 (3%), and cefipime 3 (2.5%) as seen in 314 table 6. 315 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 13 316 Table 6: showing antibiotic susceptibility patterns of pathogenic E. coli Spp 317 towards commonly used antimicrobials in Poultry. Antibiotics Resistant n (%) Intermediate Resistance n (%) Susceptible n (%) Gentamicin (GM) (10 μg/ml) 10 (8.0) 7 (6.0) 103 (86.0) Meropenem (MEM) (10 μg/ml) 4 (3) 6 (2.5) 110 (92.0) Ceftriaxone (CRO) (30 μg/ml) 57 (47.5) 5 (4.2%) 58 (48.3) Chloramphenicol (CHL) (30 μg/ml) 85 (71.0) 25 (21.0) 10 (8.0) Cefepime (CPM) (30 μg/ml) 3 (2.5) 8 (6.5) 109 (91) Ciprofloxacin (CIP) (5 μg/ml) 9 (7.5) 66 (55) 45(37.5) Erythromycin (EM) (30 μg/ml) 88 (73) 15(12.5) 17 (14.5%) Ampicillin (AMP) (10 μg/ml) 86(72) 12 (10) 18 (15) Tetracycline (OXT) (30 μg/ml) 82 (68.0) 18 (15) 20 (17.0) sulfamethoxazole-trimethoprim (SXT) (25 μg/ml) 78(65) 32 (27.0) 10 (8.0) Cefotaxime (CTX)(30µg/ml) 51(42.5) 10(8.3) 59(49.2) Ceftazidime (CTZ)(30µg/ml) 48(40) 8(6.7) 64(53.3) 318 319 Detection of ESBL (blaTEM), gene encoding resistance to commonly used antibiotics 320 used in poultry in Salmonella and Pathogenic E. coli 321 322 Out of the 18 Salmonella samples analyzed for genotypic expression, 7/18 (39%) samples 323 expressed presence of the bla TEM genes while 11 (61.1%) samples did not have this 324 gene. 325 Out of the 57 Pathogenic E. coli samples analyzed for genotypic expression, 42/57 326 (73.8%) samples expressed presence of the bla TEM genes while fifteen (26.3%) samples 327 did not have this gene. 328 DISCUSSION 329 The prevalence of selected Salmonella and pathogenic E. coli in selected poultry 330 farms 331 332 According to this study, a prevalence of 18% and 56%, respectively, was identified for 333 Salmonella and pathogenic E coli in broiler poultry farms in the Wakiso district. In line with 334 other studies carried out, this result was comparable to a study conducted by (18). This . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 14 335 revealed the prevalence of Salmonella and pathogenic E. coli as 21.1% and 56.3% in 336 Uganda. 337 However, it can be argued that this prevalence rate is low when compared to a study done 338 by (19) found an overall prevalence of 83%, of which 90.8% and 73% were from chicken 339 in Lira and Kampala districts from the antibiotic susceptibility profiles of fecal Escherichia 340 coli isolates from Dip-Litter broiler chicken in Northern and Central Uganda. 341 This discrepancy can be due to the different study sites, sample methods, poultry sector, 342 and sampling times used during the research. 343 It is worth noting that this study had a lower prevalence of Salmonella spp compared to 344 other studies such as one done by (20) in Ruiru Sub-County, Kenya which was at 28% with 345 almost similar prevalence of pathogenic E. coli of 58%. Another study on antimicrobial 346 resistance in Salmonella and Escherichia coli isolates from chicken droppings in Nairobi 347 (21) found lower levels of Salmonella (12% vs. 57% in our study) and nearly similar 348 prevalence of E. coli (57%) in the analyzed samples. 349 The differences in environmental contamination levels, poultry management practices, 350 breed, sample size, sampling, testing methodologies, and challenges in Salmonella 351 detection methods may account for this similar trend of reduced Salmonella isolation and 352 prevalence (22) or further still the practice of better bio safety and bio security practices at 353 farms overseen by the established of Kenya Accreditation society (KENAS),competitive 354 exclusion of sick birds, breeding for genetic resistance and vaccination. 355 In Uganda as evidenced from the essential veterinary medicines list, vaccines exist only in 356 private practitioners’ clinics and cannot be accessed freely by the Bio security level three 357 farmers that were of interest in this study. 358 359 The factors associated with Salmonella and Pathogenic E. coli in poultry farms in 360 Wakiso District. 361 Presence of Salmonella and pathogenic E. coli in the poultry farms was significantly 362 correlated with contact of poultry with other avian bird species such as ducks, geese, and 363 guinea fowls in the same farms and pens, as well as not frequently cleaning the poultry 364 farms by removing the manure or beddings. 365 The study further investigated other factors associated with proper poultry practices such 366 as the implementation of strict bio security interventions such as having restricted access . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 15 367 to the farmers by visitors and handling of these birds, implementation of a solid well 368 established sewer system. These, however, did not significantly increase the risk of 369 Salmonella and E. coli. This is comparable to a study conducted in Nigeria that 370 focused on the risk factors related to Salmonella spp. In broiler and layer flocks, it 371 was discovered that the presence of rodents, farm workers moving between pens, running 372 and parking trucks close to poultry farms (p<0.05) and drinking untreated water (p<0.05) 373 were all independently associated with a higher risk of Salmonella infection (23). 374 Broilers are known for consuming large amounts of feed, and this habit encourages constant 375 feces loss, raising the possibility of their environment becoming contaminated with various 376 bacterial strains (18). 377 Furthermore, many broiler farms had high stock densities, which could make environmental 378 management efforts to reduce bacteria in the houses more difficult. As a result, workers 379 (especially those handling large flocks) must be strictly supervised because it is claimed 380 that they may neglect their responsibilities for maintaining hygiene . Therefore, poor 381 management of poultry could lead to increased transmission of Salmonella and E. 382 coli in poultry. 383 384 The antimicrobial Susceptibility patterns of Salmonella and E. coli in poultry farms 385 386 The highest resistance to ampicillin was found in both Salmonella and E. coli isolates, 32 387 (80%) and 86(72%), followed by erythromycin (28%) and 88(73%) and tetracycline (27) 388 and 82(68.0%). 389 Our research was comparable to a study published by (24) and (18). Therefore, there is 390 great increase in antimicrobial resistance to the different drugs most especially ciprofloxacin 391 in Uganda. 392 According to reports from Uganda and other nations (25), tetracyclines are frequently used 393 to treat bacterial illnesses and promote animal growth (26). Therefore, it is not surprising 394 that pathogens have developed broad resistance to them. Bacteria like commensal E. coli 395 experience selection pressure as a result of ongoing exposure to antimicrobials (27). 396 In most nations, the rise in human cases of antimicrobial resistance is attributed to the 397 increase and spread of infections from poultry to humans. In this work, we discovered that 398 pathogenic E. coli and Salmonella spp. isolated from chicken in the Wakiso district had 399 high resistance to widely used antibiotics used in both people and animals. As a result, . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 16 400 greater research on AMR in Salmonella spp. and E. coli clinical isolates from poultry is 401 needed. 402 403 ESBL producing genes present among Salmonella and pathogenic E. coli isolated 404 from poultry farms. 405 406 The majority of studies on poultry have noted the presence of genes such as; blaTEM, 407 AmpC like lactamase gene, for antibiotic resistance (28), (29) and (30). A study conducted 408 in Malaysia reported a lower prevalence of blaTEM (31) while a study in British Columbia, 409 2007 reported slightly higher levels of the blaTEM gene, being 81.5 and 80% of 410 amoxicillin and ampicillin resistant E.coli and Salmonella spp. isolates (32). 411 Therefore, the community’s health is at risk because of the possibility that antimicrobial 412 resistance genes in poultry waste will spread to humans and other fowl. 413 414 CONCLUSION 415 416 The two most significant food-borne pathogens of public health concern linked to poultry 417 are still Salmonella spp. and Escherichia coli, and it is evident from this study with a 418 prevalence of 18% and 56% respectively. These bacteria have resistant genes associated 419 with them seen in 38.9% and 73.8% Salmonella and pathogenic E. coli samples. 420 421 422 Limitations 423 424 i. Our focus in this study was strictly broiler poultry that were about to enter the food chain, 425 this is does not paint a full picture in terms of the overall burden of the disease in poultry 426 including all other avian birds such as layers, geese, guinea fowls and ducks to 427 effectively understand the disease transmission dynamics and effect policies that will 428 effectively halt further spread. 429 ii. Only one gene blaTEM was focused on during this study and it would be vital to conduct 430 different genetic manipulations of the same bacterial DNA to targeting different ESBL 431 genes such as bla CTM, bla SHV etc. 432 433 Recommendations 434 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint 17 435 Based on the above the study findings, its pertinent that government of Uganda should 436 strengthen the antimicrobial stewardship program and ensure that it is supported to carry 437 out its mandate of coordination that supports the proper use of antimicrobials (including 438 antibiotics), improves patient outcomes, lowers microbial resistance, and limits the spread 439 of diseases brought on by multidrug-resistant organisms, the organization needs help. 440 This should be achieved through the one health platform, a forum that brings together all 441 key stakeholders from the four different line ministries of Health, Ministry of Agriculture 442 Animal Industries and Fisheries, Ministry of Water and sanitation and Ministry of tourism, 443 trade, and antiquities. 444 445 DECLARATION 446 447 Conflicts of Interest 448 The authors confirm no conflicts of interest pertaining the publication of this article. 449 450 Author contributions 451 TS and KT developed the study concept, TS, JCB and NPP provided input in data collection. 452 TS and JCB analysed the data. 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CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted August 16, 2024. ; https://doi.org/10.1101/2024.08.16.24312101doi: medRxiv preprint