Stochastic processes drive divergence of bacterial and fungal communities in sympatric wild insect species despite sharing a common diet.

Arthropods harbor complex microbiota that play a pivotal role in host fitness. While multiple factors, like host species and diet, shape microbiota in arthropods, their impact on community assembly in wild insects remains largely unknown. In this study, we surveyed bacterial and fungal community assembly in nine sympatric wild insect species that share a common citrus fruit diet. Source tracking analysis suggested that these insects acquire some bacteria and fungi from the citrus fruit with varying degrees. Although sharing a common diet led to microbiota convergence, the diversity, composition, and network of both bacterial and fungal communities varied significantly among surveyed insect groups. Null model analysis indicated that stochastic processes, particularly dispersal limitation and drift, are primary drivers of structuring insect bacterial and fungal communities. Importantly, the influence of each community assembly process varied strongly depending on the host species. Thus, we proposed a speculative view that the host specificity of the microbiome and mycobiome assembly is widespread in wild insects despite sharing the same regional species pool. Overall, this research solidifies the importance of host species in shaping microbiomes and mycobiomes, providing novel insights into their assembly mechanisms in wild insects. IMPORTANCE: Since the microbiome has been shown to impact insect fitness, a mechanistic understanding of community assembly has potentially significant applications but remains largely unexplored. In this paper, we investigate bacterial and fungal community assembly in nine sympatric wild insect species that share a common diet. The main findings indicate that stochastic processes drive the divergence of microbiomes and mycobiomes in nine sympatric wild insect species. These findings offer novel insights into the assembly mechanisms of microbiomes and mycobiomes in wild insects.

Mechanisms of bacterial and fungal community assembly in leaf miners during transition from natural to laboratory environments.

Environmental heterogeneity partly drives microbial succession in arthropods, while the microbial assembly mechanisms during environmental changes remain largely unknown. Here, we explored the temporal dynamics and assembly mechanisms within both bacterial and fungal communities in Liriomyza huidobrensis (Blanchard) during the transition from field to laboratory conditions. We observed a decrease in bacterial diversity and complexity of bacterial-fungal co-occurrence networks in leaf miners transitioning from wild to captive environments. Both neutral and null models revealed that stochastic processes, particularly drift (contributing over 70%), play a crucial role in governing bacterial and fungal community assembly. The relative contribution of ecological processes such as dispersal, drift, and selection varied among leaf miners transitioning from wild to captive states. Furthermore, we propose a hypothetical scenario for the assembly and succession of microbial communities in the leaf miner during the short- and long-term transition from the wild to captivity. Our findings suggest that environmental heterogeneity determines the ecological processes governing bacterial and fungal community assembly in leaf miners, offering new insights into microbiome and mycobiome assembly mechanisms in invasive pests amidst environmental change.

[Detection of organophosphorus pesticide residue on the surface of apples using SERS].

Traditional pesticide residue detection methods are usually complicated, time-consuming, and destructive. Rapid, nondestructive, online real-time is the development direction of the pesticide testing. In the present paper, we use surface enhanced Raman spectroscopy (SERS) technique to detect the organophosphorus pesticide residue of phorate and fenthion on apple to investigate a fast, nondestructive detection method for the pesticide of phorate and tiguron on apples. The results show that the characteristic frequencies of the two organophosphorus pesticides are easier to identify using surface-enhanced Raman spectroscopy. We select Raman signal at 728 cm(-1) for phorate and that at 1 512 cm(-1) for fenthion as target peak for quantitative analysis, and use an internal standard to establish phorate and fenthion linear regression model. This method can be used as a quantitative analysis reference of phorate and fenthion.

[Surface enhanced Raman spectroscopy (SERS) of saliva for the diagnosis of lung cancer].

Surface enhanced Raman spectroscopy (SERS) has shown the advantage of detecting low concentration biofluids presently. Saliva SERS of 21 lung cancer patients and 22 normal people were measured and differentiated in the present paper. Intensities of most peaks of lung cancer patients are weaker than that of normal people, while some stronger but with a small change rate. Those peaks were assigned to proteins and nucleic acids which indicate a corresponding decrease of those substances in saliva. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to deduce and discriminate the two groups of data, resulting in accuracy, sensitivity, and specificity being 84%, 94%, and 81%, respectively.