Chris Lamberigts

A PKS/NRPS/FAS Hybrid Gene Cluster from Serratia plymuthica RVH1 Encoding the Biosynthesis of Three Broad Spectrum, Zeamine-Related Antibiotics

Serratia plymuthica strain RVH1, initially isolated from an industrial food processing environment, displays potent antimicrobial activity towards a broad spectrum of Gram-positive and Gram-negative bacterial pathogens. Isolation and subsequent structure determination of bioactive molecules led to the identification of two polyamino antibiotics with the same molecular structure as zeamine and zeamine II as well as a third, closely related analogue, designated zeamine I. The gene cluster encoding the biosynthesis of the zeamine antibiotics was cloned and sequenced and shown to encode FAS, PKS as well as NRPS related enzymes in addition to putative tailoring and export enzymes. Interestingly, several genes show strong homology to the pfa cluster of genes involved in the biosynthesis of long chain polyunsaturated fatty acids in marine bacteria. We postulate that a mixed FAS/PKS and a hybrid NRPS/PKS assembly line each synthesize parts of the backbone that are linked together post-assembly in the case of zeamine and zeamine I. This interaction reflects a unique interplay between secondary lipid and secondary metabolite biosynthesis. Most likely, the zeamine antibiotics are produced as prodrugs that undergo activation in which a nonribosomal peptide sequence is cleaved off.

The MC4R c.893G > A mutation: A marker for growth and leanness associated with boar taint odour in Belgian pig breeds

Since surgical castration of male piglets without anaesthesia is under heavy societal pressure, finding a sustainable solution to reduce boar taint has become urgent. One way to circumvent this animal welfare violation is raising entire male pigs whilst selecting against the tainted phenotype through marker-assisted selection. Since slaughtering at a lower weight is often suggested to reduce boar taint, selection using a marker for that trait could be a promising strategy. Therefore, in this study a melanocortin 4 receptor (MC4R) mutation, frequently described in different pig breeds as marker for fat content, weight gain and feed intake, was examined in relation to boar taint in pig breeds used in Belgian pig farms. Although results suggest an association between this mutation and a boar taint odour score assigned by experts, no association was found between the mutation and the concentration of the individual chemical boar taint components androstenone, skatole and indole.

Total Synthesis of Septocylindrin B and C-Terminus Modified Analogues

The total synthesis is reported of the peptaibol Septocylindrin B which is related to the well documented channel forming peptaibol antibiotic Alamethicin. Several analogues were synthesized with a modified C-terminus, to investigate the SAR of the terminal residue Phaol. All these peptides were tested for their membrane perturbation properties by fluorescent dye leakage assay and for their antibacterial activity.

Sensitivity of heat detection attentions and their relation with the moment of LH surge in dairy cows

The sensitivity of an estrus detection system and the consistency of alarms relative to ovulation determine its value for a farmer. The objective of this study was to compare four different heat detection systems for their ability to detect heat and predict the moment of the LH surge in a single herd during the same study period. This comparison, in which the moment of the LH surge was used as an indicator for ovulation, allowed for the objective evaluation of each system and the potential for optimizing the fertility management on farm. The four systems were traditional visual observation, an activity-based system and two progesterone-based methods: (1) Herd Navigator™ and (2) a novel algorithm which combines a mathematical model and synergistic control. The latter algorithm also allowed to test whether using the mathematical model could improve the relation with the LH surge. First, the systems were compared in terms of sensitivity and positive predictive value for heat detection. Then, the time interval between the attentions and the LH surge was investigated and compared based on their range and SD. Heat attentions based on visual observations had the lowest sensitivity to detect heat (40%), and were noted from 4 hours before until 5 hours after the LH surge (range 9 hours, SD 4 hours), indicating a strong relation. Activity-attentions proved more sensitive (80%). They had the least accurate relation with the moment of the LH surge and were observed from 39 hours before until 8 hours after it (range 47 hours, SD 16 hours). Attentions based on milk progesterone measurements correctly identified all estrous periods. Herd Navigator™ attentions system were followed by the LH surge after 22 to 66 hours (range of 45 hours, SD 11 hours). The model-based approach generated attentions 49 to 81 hours (range 33 hours, SD 11 hours) before the LH surge. As detection of the LH surge was very labor-intensive, only a limited number of potential heat periods could be studied. For some of the methods (e.g. visual observations), the sensitivity restricted the number of cases even more. Nevertheless, the approach ensured an objective comparison between relevant heat detection systems in a commercially representative setting. Accordingly, this study helps to place larger studies linking heat detection and ovulation into perspective and shows the potential of new P4-interpreting algorithms, thereby highlighting the need for further research.Both estrus detection and timely insemination are important factors in optimizing fertility management. The latter is dependent on ovulation time, which is preceded by the LH surge. The performance of an estrus detection system based on activity and based on milk progesterone was evaluated and the timing of the alerts was contrasted against the moment of the LH surge. Activity alerts had a sensitivity of 83% and a positive predictive value of 66%; the LH surge followed average 9.4 ± 16.1 hours later. Using milk progesterone, one can reliably detect luteolysis, which is followed by the LH surge after 62 ± 12 hours.Both heat detection and timely insemination contribute to the optimization of fertility management on farm. In this study, 4 systems were compared for their ability to accurately detect heat and relate to the LH surge preceding ovulation in dairy cows. As the moment of LH surge has been reported to correlate strongly with time of ovulation, the potential to predict the optimal insemination can in this way be evaluated. The systems included were the traditional visual observation of heat, activity attentions and 2 progesterone-based methods. For the latter, it was also investigated whether the prediction of the LH surge could be improved by fitting a longitudinal model to the progesterone data. First, the systems were compared in terms of sensitivity and positive predictive value for heat detection. Then, the time interval between the attentions and the LH surge was investigated. The range on this interval was used as main criterion to evaluate the time-relation between the heat attention and the LH surge. The smaller this range, the better the correlation with the LH surge, and accordingly, ovulation. Heat attentions based on visual observations were noted from 4 hours before until 5 hours after the LH surge (range of 9 hours), indicating a high correlation. However, they also had the lowest sensitivity to detect heat (40%), making it less useful on-farm. Using activity-attentions proved more sensitive (80%), but was less accurate. Moreover, these attentions had the least accurate correlation with the moment of the LH surge and were observed from 39 hours before until 8 hours after it (range of 47 hours). Attentions based on milk progesterone measurements through the detection of luteolysis preceding a follicular phase correctly identified all estrous periods. Alarms generated when the smoothed progesterone level crossed a 5 ng/mL threshold, were followed by the LH surge after 21.6 to 66.4 hours (range of 44.8 hours). The model-based approach performed slightly better with attentions generated 48.8 to 81.2 hours (range 32.9 hours) before the LH surge.

A novel system for on-farm fertility monitoring based on milk progesterone

Timely identification of a cows reproduction status is essential to minimize fertility-related losses on dairy farms. This includes optimal estrus detection, pregnancy diagnosis, and the timely recognition of early embryonic death and ovarian problems. On-farm milk progesterone (P4) analysis can indicate all of these fertility events simultaneously. However, milk P4 measurements are subject to a large variability both in terms of measurement errors and absolute values between cycles. The objective of this paper is to present a newly developed methodology for detecting luteolysis preceding estrus and give an indication of its on-farm use. The innovative monitoring system presented is based on milk P4 using the principles of synergistic control. Instead of using filtering techniques and fixed thresholds, the present system employs an individually on-line updated model to describe the P4 profile, combined with a statistical process control chart to identify the cows fertility status. The inputs for the latter are the residuals of the on-line updated model, corrected for the concentration-dependent variability that is typical for milk P4 measurements. To show its possible use, the system was validated on the P4 profiles of 38 dairy cows. The positive predictive value for luteolysis followed by estrus was 100%, meaning that the monitoring system picked up all estrous periods identified by the experts. Pregnancy or embryonic mortality was characterized by the absence or detection of luteolysis following an insemination, respectively. For 13 cows, no luteolysis was detected by the system within the 25 to 32 d after insemination, indicating pregnancy, which was confirmed later by rectal palpation. It was also shown that the system is able to cope with deviating P4 profiles having prolonged follicular or luteal phases, which may suggest the occurrence of cysts. Future research is recommended for optimizing sampling frequency, predicting the optimal insemination window, and establishing rules to detect problems based on deviating P4 patterns.