Bock, Clive

Citrus huanglongbing (HLB), associated with the bacterium ‘Candidatus Liberibacter asiaticus’ and spread by the Asian citrus psyllid (Diaphorina citri; ACP), poses a significant threat to California’s citrus industry. First identified in Los Angeles in 2012, HLB has since spread through residential areas across Southern California. A risk-based survey (RBS) model has been developed to improve HLB surveillance and intervention. Within this framework, model components change as HLB dynamics shift, requiring regular updates to maintain data accuracy and model reliability. Disease spread is influenced by natural factors, such as ACP establishment and confirmed HLB locations, as well as human-mediated factors like global mobility (travel introduction from HLB-infected countries), transportation of citrus materials, nurseries, packinghouses, farmers’ markets, and proximity to private or otherwise inaccessible lands. Human-mediated risk factors account for approximately 26.3% (18.4 to 38.4%) of HLB incidence across different years, and natural causes predominantly explain the remaining 73.7% (61.6 to 81.7%). Notably, global mobility was crucial for early HLB detection in new areas, whereas ACP density strongly correlated with disease spread once established. A retrospective analysis from 2015 to 2022 evaluated the RBS model’s performance, showing a predictive power of 88 to 97%, which confirms its validity for developing targeted interventions and early detection strategies in California.

AbstractCandidatusLiberibacter asiaticus (Las) is one of the causal agents of citrus huanglongbing (HLB) epidemics worldwide. Due to its fastidious nature, intracellular and systemic infection, detecting Las at early and/or low-titer infection, as well as differentiating between live or dead cells in the host psyllids and citrus plants is critical for effective HLB management. To achieve both sensitive Las detection and differentiation, we employed one-step reverse transcription-quantitative PCR (RT-qPCR) using total nucleic acids as template. This method allows use of both Las 16S rRNA and rDNA as template in the same reaction and increases detection sensitivity by up to 1000-fold in comparison with quantitative PCR (qPCR). The increased sensitivity significantly reduces false negative detection and detects the otherwise undetectable low-titer Las infections. Furthermore, the greater the abundance of 16S rRNA present in the samples, the bigger the Ct gap obtained between RT-qPCR and qPCR results. The numerical Ct gap can be used to deduce relative Las cellular activity and indirectly infer whether cells are alive or dead. In addition, this comparative detection method also can be used to select inoculum and monitor relative cell activity duringin vitroLas culture and evaluate the effectiveness of antimicrobial treatments against Las bacteria.