An application of reflectance spectroscopy to differentiate of entomopathogenic fungi species

Multidimensional discriminant analysis of species, strains and culture age of closely related entomopathogenic fungi using reflectance spectroscopy

The diversity of fungal strains is influenced by genetic and environmental factors, growth conditions and mycelium age, and the spectral features of fungal mycelia are associated with their biochemical, physiological, and structural traits. This study investigates whether intraspecific differences can be detected in two closely related entomopathogenic species, namely Cordyceps farinosa and Cordyceps fumosorosea, using ultraviolet A to shortwave infrared (UVA-SWIR) reflectance spectra. Phylogenetic analysis of all strains revealed a high degree of uniformity among the populations of both species. The characteristics resulting from variation in the species, as well as those resulting from the age of the cultures were determined. We cultured fungi on PDA medium and measured the reflectance of mycelia in the 350-2500 nm range after 10 and 17 days. We subjected the measurements to quadratic discriminant analysis (QDA) to identify the minimum number of bands containing meaningful information. We found that when the age of the fungal culture was known, species represented by a group of different strains could be distinguished with no more than 3-4 wavelengths, compared to 7-8 wavelengths when the age of the culture was unknown. At least 6-8 bands were required to distinguish cultures of a known species among different age groups. Distinguishing all strains within a species was more demanding: at least 10 bands were required for C. fumosorosea and 21 bands for C. farinosa. In conclusion, fungal differentiation using point reflectance spectroscopy gives reliable results when intraspecific and age variations are taken into account.

Detection of the pathogenic fungus Cordyceps farinosa in the Thitarodes armoricanus soil-rearing environment based on nucleic acid targets

Cordyceps farinosa, an entomopathogenic fungus, infects and leads to high mortality of Thitarodes armoricanus larvae, which die soon after the infection of C. farinose, usually before the colonization of Ophiocordyceps sinensis owing to competitive inhibition and fruiting body formation. Therefore, monitoring C. farinosa in the O. sinensis cultivation environment is critical for minimizing the C. farinosa infection-induced losses. In this study, we initially designed a PCR primer pair (Tar-1F/Tar-1R) through open reading frame prediction and homology comparison of the C. farinosa genome sequence. This primer pair can detect both C. farinosa and Samsoniella hepiali. To further distinguish, primers (ITS5-172/ITS4-95) were then designed to selectively amplify the large ribosomal subunit sequences in the C. farinosa genome. All these primers were applied in combination for detection of C. farinosa in soil samples. The sensitivity reached a detection limit of 1 × 10⁶ spores/g soil. In addition, these primers can detect the presence of C. farinosa in dead T. armoricanus larval samples. This newly established rapid detection method provides important information for C. farinosa control during O. sinensis cultivation.

Close-Range Thermography and Reflectance Spectroscopy Support In Vitro and In Vivo Characterization of Colletotrichum spp. Isolates from Mango Fruits

Colletotrichum causing anthracnose in mango is known for its variable virulence that may have an effect on disease development and efficacy of management strategies. In this study, we characterized Colletotrichum spp. isolated from mango fruits under in vitro and in vivo conditions using close-range thermography and reflectance spectroscopy. Twenty-six isolates were phylogenetically characterized to ascertain species using the internal transcribed spacer sequence. Virulence, spectral (in vivo and in vitro), and thermographic responses (in vivo) of these isolates were analyzed. Isolates were grouped into the Colletotrichum gloeosporioides species complex and classified into eight morphotypes. Mycelial growth, conidia production, sporulation abundance, and area under disease progress curve (AUDPC) varied largely among isolates. Disease symptoms were observed 4 days after inoculation (dai), and, for most morphotypes, changes in tissue temperature were registered at 11 dai, with the greatest decrease at 14 dai with pathogen sporulation. In vitro and in vivo morphotypes shared changes in the spectrum range, and main variations were found in the number of informative spectral bands. In vivo average gross reflectance was higher in disease-inoculated tissue than in healthy uninoculated tissue. Morphotype responses varied depending on AUDPC values and postinoculation time. Discriminant analysis of the spectral response using principal component analysis and partial least squares regression explained 94 to 96.3 and 98 to 99.9% of the variance from in vitro and in vivo tests, respectively. Spectral markers were obtained for four distinct morphotype groups. We found three (550 to 650, 650.1 to 790, and 1,300 to 1,400 nm) and two (520 to 830 and 1,100 to 1,450 nm) regions with highly (P < 0.05) discriminant spectral bands for diseased fruits and morphotype characterization.

Reflectance spectroscopy and machine learning as a tool for the categorization of twin species based on the example of the Diachrysia genus

In our work we used noninvasive point reflectance spectroscopy in the range from 400 to 2100 nm coupled with machine learning to study scales on the brown and golden iridescent areas on the dorsal side of the forewing of Diachrysia chrysitis and D. stenochrysis. We used our approach to distinguish between these species of moths. The basis for the study was a statistically significant collection of 95 specimens identified based on morphological feature and gathered during 23 years in Poland. The numerical part of an experiment included two independent discriminant analyses: stochastic and deterministic. The more sensitive stochastic approach achieved average compliance with the species identification made by entomologists at the level of 99-100%. It demonstrated high stability against the different configurations of training and validation sets, hence strong predictors of Diachrysia siblings distinctiveness. Both methods resulted in the same small set of relevant features, where minimal fully discriminating subsets of wavelengths were three for glass scales on the golden area and four for the brown. The differences between species in scales primarily concern their major components and ultrastructure. In melanin-absent glass scales, this is mainly chitin configuration, while in melanin-present brown scales, melanin reveals as an additional factor.

Enhanced sensitivity and efficiency of detection of Staphylococcus aureus based on modified magnetic nanoparticles by photometric systems

Staphylococcus aureus is an important infectious factor in the food industry and hospital infections. Many methods are used for detecting bacteria but they are mostly time-consuming, poorly sensitive. In this study, a nano-biosensor based on iron nanoparticles (MNPs) was designed to detect S. aureus. MNPs were synthesized and conjugated to Biosensors. Then S. aureus was lysed and nano-biosensor (MNP-TiO₂-AP-SMCC-Biosensors) was added to the lysed bacteria. After bonding the bacterial genome to the nano-biosensor, MNPs were separated by a magnet. Bacterial DNA was released from the surface of nano-biosensor and researched by Nano-drop spectrophotometry. The results of SEM and DLS revealed that the size of MNPs was 20-25 nm which increased to 38-43 nm after modification and addition of biosensors. The designed nano-biosensor was highly sensitive and specific for the detection of S. aureus. The limit of detection (LOD) was determined as 230 CFU mL^-1. There was an acceptable linear correlation between bacterial concentration and absorption at 3.7 × 10²-3.7× 10⁷ whose linear diagram and regression was Y = 0.242X + 2.08 and R² = .996. Further, in the presence of other bacteria as a negative control, it was absolutely specific. The sensitivity of the designed nano-biosensor was investigated and compared through PCR.

Functionalization of anti-Brucella antibody based on SNP and MNP nanoparticles for visual and spectrophotometric detection of Brucella

An Immuno-Nano-Biosensor with high sensitivity was designed based on iron and silica nanoparticles to detect B. abortus. Briefly explain, primary polyclonal antibody (IgG₁) was conjugated on surface magnetic nanoparticles (MNPs) to form MNP-IgG₁. Secondary polyclonal antibody (IgG₂) and Horseradish Peroxidase enzyme were conjugated on silica nanoparticles (SNPs) to form HRP-SNP-IgG₂. HRP-SNP-IgG₂. MNP-IgG₁ and HRP-SNP-IgG₂ were added to B. abortus. The MNP-IgG₁-B.abortus-IgG₂-SNP-HRP complex was isolated from the reaction mixture using a magnet. After that, tetramethylbenzidine was added to the complex. The reaction was stopped with HCl and investigated using UV-Vis spectrophotometry. The nanoparticles' structure and size were investigated using SEM and DLS. Immuno-Nano-Biosensor sensitivity and specificity were determined. The SEM and DLS results indicated that the SNPs, MNPs, HRP-SNP-IgG₂ and MNP-IgG₁ size and structure were 35, 44, 60 and 56 nm, respectively. In addition, a good linear correlation was observed at 10²-10⁷ CFU mL^-1 concentrations, which their linear equation and regression were Y = 0.3× + 0.18 and R² 0.982, respectively. The limitation of detecting B. abortus was 160 CFU mL^-1. Finally, the results demonstrated that those designed Immuno-Nano-Biosensor could be specifically detected B. abortus and B. melitensis in real samples.

Extended Multiplicative Signal Correction for Infrared Microspectroscopy of Heterogeneous Samples with Cylindrical Domains

Optical scattering corrections are invoked to computationally distinguish between scattering and absorption contributions to recorded data in infrared (IR) microscopy, with a goal to obtain an absorption spectrum that is relatively free of the effects of sample morphology. Here, we present a modification of the extended multiplicative signal correction (EMSC) approach that allows for spectral recovery from fibers and cylindrical domains in heterogeneous samples. The developed theoretical approach is based on exact Mie theory for infinite cylinders. Although rigorous Mie theory implies utilization of comprehensive and time-consuming calculations, we propose to change the workflow of the original EMSC algorithm to minimize extensive calculations for each recorded spectrum at each iteration step. This makes the modified EMSC approach practical for routine use. First, we tested our approach using synthetic data derived from a rigorous model of scattering from cylinders in an IR microscope. Second, we applied the approach to Fourier transform IR (FT-IR) microspectroscopy data recorded from filamentous fungal and cellulose samples with pronounced fiber-like shapes. While the corrected spectra show greatly reduced baseline offsets and consistency, strongly absorbing regions of the spectrum require further refinement. The modified EMSC algorithm broadly mitigates the effects of scattering, offering a practical approach to more consistent and accurate spectra from cylindrical objects or heterogeneous samples with cylindrical domains.