henhaobio
Sign in

bioRxivMolecular BiologyPreprint

Comparative RT-qPCR and qPCR reveals early infection, low-titer infection, and relative cell activity of the HLB bacterium, Candidatus Liberibacter asiaticus

Rachel Patterson, Desen Zheng, Weiqi LuoiD, Zhanao DengiD, Clive Howard BockiD, Ruhui LiiD, Yongping DuaniD

PDFDOI

Abstract

Candidatus Liberibacter 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 during in vitro Las culture and evaluate the effectiveness of antimicrobial treatments against Las bacteria.

Citations
0

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMaheshwari '20Sanches '25Rocha '19Lovelace '24Bernardini '22Perez-Lopez '20
75% semantic matchMicrobiology
Y. Maheshwari, V. Selvaraj, K. Godfrey+2 more·bioRxiv·Nov 3, 2020