Fungal biomarkers are detectable in Martian rock-analogues after space exposure: implications for the search of life on Mars

Mars is a primary target of astrobiological interest: its past environmental conditions may have been favourable to the emergence of a prebiotic chemistry and, potentially, biological activity. In situ exploration is currently underway at the Mars surface, and the subsurface (2 m depth) will be explored in the future ESA ExoMars mission. In this context, BIOlogy and Mars EXperiment was performed to evaluate the stability and detectability of organic biomarkers under space and Mars-like conditions. Our data suggested that some target molecules, namely melanin, azelaic acid and nucleic acids, can be detected even after 16 months exposure to Low Earth Orbit conditions by multidisciplinary approaches. We used the same techniques as onboard the ExoMars rover, as Raman and infrared spectroscopies and gas chromatograph-mass spectrometer, and polymerase chain reaction even if this is not planned for the imminent mission to Mars. These results should be taken into account for future Mars exploration.

Fungal Biomarkers Stability in Mars Regolith Analogues after Simulated Space and Mars-like Conditions

The discovery of life on other planets and moons in our solar system is one of the most important challenges of this era. The second ExoMars mission will look for traces of extant or extinct life on Mars. The instruments on board the rover will be able to reach samples with eventual biomarkers until 2 m of depth under the planet’s surface. This exploration capacity offers the best chance to detect biomarkers which would be mainly preserved compared to samples on the surface which are directly exposed to harmful environmental conditions. Starting with the studies of the endolithic meristematic black fungus Cryomyces antarcticus, which has proved its high resistance under extreme conditions, we analyzed the stability and the resistance of fungal biomarkers after exposure to simulated space and Mars-like conditions, with Raman and Gas Chromatography–Mass Spectrometry, two of the scientific payload instruments on board the rover.

Diagnosis of Pneumonia Due to Invasive Molds

Pneumonia is the most common presentation of invasive mold infections (IMIs), and is pathogenetically characterized as angioinvasion by hyphae, resulting in tissue infarction and necrosis. Aspergillus species are the typical etiologic cause of mold pneumonia, with A. fumigatus in most cases, followed by the Mucorales species. Typical populations at risk include hematologic cancer patients on chemotherapy, bone marrow and solid organ transplant patients, and patients on immunosuppressive medications. Invasive lung disease due to molds is challenging to definitively diagnose based on clinical features and imaging findings alone, as these methods are nonspecific. Etiologic laboratory testing is limited to insensitive culture techniques, non-specific and not readily available PCR, and tissue biopsies, which are often difficult to obtain and impact on the clinical fragility of patients. Microbiologic/mycologic analysis has limited sensitivity and may not be sufficiently timely to be actionable. Due to the inadequacy of current diagnostics, clinicians should consider a combination of diagnostic modalities to prevent morbidity in patients with mold pneumonia. Diagnosis of IMIs requires improvement, and the availability of noninvasive methods such as fungal biomarkers, microbial cell-free DNA sequencing, and metabolomics-breath testing could represent a new era of timely diagnosis and early treatment of mold pneumonia.

Performance, Correlation and Kinetic Profile of Circulating Serum Fungal Biomarkers of Invasive Aspergillosis in High-Risk Patients with Hematologic Malignancies

As conventional microbiological documentation of invasive aspergillosis (IA) is difficult to obtain, serum fungal biomarkers are important adjunctive diagnostic tools. Positivity rates and the kinetic profiles of galactomannan (GM), 1,3-β-D-glucan (BDG) and Aspergillus DNA (PCR) were studied in high-risk patients with hematologic malignancies. GM, BDG and PCR data from serial serum specimens (n = 240) from 93 adult hematology patients with probable (n = 8), possible (n = 25) and no (n = 60) IA were retrospectively analyzed. Positivity rates and sensitivity/specificity/positive/negative predictive values (NPV) of each fungal biomarker alone and in combination were estimated. The three markers were compared head-to-head and correlated with various biochemical, demographic and patient characteristics. The positivity rates for patients with probable/possible/no IA were 88%/8%/0 % for GM (X2 = 55, p < 0.001), 62%/46%/35% for BDG (X2 = 2.5, p = 0.29), 62%/33%/27% for PCR (X2 = 3.9, p = 0.15), 50%/4%/0% for GM + BDG and GM + PCR (X2 = 31, p < 0.001), 50%/8%/22% for BDG + PCR (X2 = 6.5, p = 0.038) and 38%/4%/0% for GM + BDG + PCR (X2 = 21, p < 0.001). Higher agreement (76%) and negative correlation (rs = -0.47, p = 0.0017) was found between GM index and PCR Ct values. The sensitivity and NPV was 45-55% and 90-92% when biomarkers assessed alone and increased to 75-90% and 93-97%, respectively when combined. Weak significant correlations were found between GM, PCR and BDG results with renal/liver function markers (r = 0.11–0.57) with most GM+ and PCR+ samples found in the first and second week of clinical assessment, respectively and BDG later on. Different positivity rates, time profiles and performances were found for the three biomarkers advocating the combination of GM with PCR for the early diagnosis of IA, whereas the high NPV of combined biomarkerscould help excluding IA.

New clinical algorithm including fungal biomarkers to better diagnose probable invasive pulmonary aspergillosis in ICU

Background The classification of invasive pulmonary aspergillosis (IPA) issued by the European Organization for the Research and Treatment of Cancer/Mycoses Study Group Education and Research Consortium (EORTC/MSGERC) is used for immunocompromised patients. An alternative algorithm adapted to the intensive care unit (ICU) population has been proposed (AspICU), but this algorithm did not include microbial biomarkers such as the galactomannan antigen and the Aspergillus quantitative PCR. The objective of the present pilot study was to evaluate a new algorithm that includes fungal biomarkers (BM-AspICU) for the diagnosis of probable IPA in an ICU population. Patients and methods Data from 35 patients with pathology-proven IPA according to European Organization for the Research and Treatment of Cancer/Mycosis Study Group (EORTC/MSGERC)-2008 criteria were extracted from the French multicenter database of the Invasive Fungal Infections Surveillance Network (RESSIF). The patients were investigated according to the AspICU algorithm, and the BM-AspICU algorithm in analyzing the clinical, imaging, and biomarker data available in the records, without taking into account the pathology findings. Results Eight patients had to be excluded because no imaging data were recorded in the database. Among the 27 proven IPAs with complete data, 16 would have been considered as putative IPA with the AspICU algorithm and 24 would have been considered as probable IPA using the new algorithm BM-AspICU. Seven out of the 8 patients with probable BM-AspICU IPA (and not classified with the AspICU algorithm) had no host factors and no Aspergillus-positive broncho-alveolar lavage fluid (BALF) culture. Three patients were non-classifiable with any of the two algorithms, because they did not have any microbial criteria during the course of the infection, and diagnosis of proven aspergillosis was done using autopsy samples. Conclusion Inclusion of biomarkers could be effective to identify probable IPA in the ICU population. A prospective study is needed to validate the routine application of the BM-AspICU algorithm in the ICU population.

Comparison of β-D-Glucan and Galactomannan in Serum for Detection of Invasive Aspergillosis: Retrospective Analysis with Focus on Early Diagnosis

The early diagnosis of invasive aspergillosis (IA) relies mainly on computed tomography imaging and testing for fungal biomarkers such as galactomannan (GM). We compared an established ELISA for the detection of GM with a turbidimetric assay for detection of the panfungal biomarker β-D-glucan (BDG) for early diagnosis of IA. A total of 226 serum specimens from 47 proven and seven probable IA cases were analysed. Sensitivity was calculated for samples obtained closest to the day of IA-diagnosis (d0). Additional analyses were performed by including samples obtained during the presumed course of disease. Most IA cases involved the respiratory system (63%), and Aspergillus fumigatus was the most frequently isolated species (59%). For proven cases, sensitivity of BDG/GM analysis was 57%/40%. Including all samples dating from –6 to +1 weeks from d0 increased sensitivities to 74%/51%. Sensitivity of BDG testing was as high as or higher than GM testing for all subgroups and time intervals analysed. BDG testing was less specific (90–93%) than GM testing (99–100%). Combining BDG and GM testing resulted in sensitivity/specificity of 70%/91%. Often, BDG testing was positive before GM testing. Our study backs the use of BDG for diagnosis of suspected IA. We suggest combining BDG and GM to improve the overall sensitivity.

Fungal mycoflora dysbiosis in gastric cancer

Background: Bacterial infection is associated with gastric carcinogenesis. However, the relationship between nonbacterial components and gastric cancer (GC) has not been fully explored. We aimed to characterize the fungal mycobiome in GC.Results: We observed significant gastric fungal dysbiosis in GC. Principal component analysis revealed separate clusters for the GC and control groups, and Venn diagram analysis indicated that the GC group showed a lower OTU abundance than the control. At the genus level, the abundances of 15 fungal biomarkers distinguished the GC group from the control, of which Candida (p = 0.000246) and Alternaria (p = 0.00341) were enriched in GC, while Saitozyma (p = 0.002324) and Thermomyces (p = 0.009158) were decreased. Combining the results of Welch’s t test and Wilcoxon rank sum test, C. albicans was significantly elevated in GC. The species richness Krona pie chart further revealed that C. albicans occupied 22% and classified GC from the control with an area under the receiver operating curve (AUC) of 0.743. Random forest analysis also confirmed that C. albicans could serve as a biomarker with a certain degree of accuracy. Moreover, compared with that of the control, the alpha diversity index was significantly reduced in the GC group. The Jaccard distance index and the Bray abundance index of the PCoA clarified separate clusters between the GC and control groups at the species level (p = 0.00051). Adonis (PERMANOVA) analysis and ANOVA showed that there were significant differences in fungal structure among groups (p = 0.001). Finally, FUNGuild functional classification predicted that saprotrophs were the most abundant taxa in the GC group.Conclusions: This study revealed GC-associated mycobiome dysbiosis characterized by an altered fungal composition and ecology and demonstrated that C. albicans can be a fungal biomarker for GC. In addition, C. albicans may mediate GC by reducing the diversity and richness of fungi in the stomach, contributing to the pathogenesis of GC.

Soil texture determines the microbial processing from litter to POM and MAOM in the detritussphere

&lt;p&gt;Soil texture and microorganisms are key drivers controlling the fate of organic matter (OM) originating from decaying plant litter, and thus the stabilization of soil organic matter (SOM). However, the understanding of the mutual interactions between microbial litter decay and soil structure formation controlled by different soil textures remains incomplete. We monitored the fate of litter-derived OM (using &lt;sup&gt;13&lt;/sup&gt;C isotopic enrichment) from decaying litter (shredded maize leaves) to microorganisms and SOM in two differently textured soils (sand and loam). The two soils were incubated with litter mixed in the top layer in microcosms for 95 days during which regular CO&lt;sub&gt;2&lt;/sub&gt; and &lt;sup&gt;13&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt; measurements were conducted. After the incubation, each microcosm was divided in three to separate a top, center and bottom layer. Using a physical soil fractionation scheme, we assessed the fate of litter-derived OM to free and occluded particulate OM (POM), as well as mineral associated OM (MAOM). All SOM fractions were analysed with respect to their mass distribution, C, N, and &lt;sup&gt;13&lt;/sup&gt;C contents, and for their chemical composition using compound-specific &lt;sup&gt;13&lt;/sup&gt;C-CPMAS NMR spectroscopy. The effects of contrasting textures on the total microbial community structure were studied using phospholipid fatty acids (PLFA) and the incorporation of litter-derived C into individual PLFAs was assessed via &lt;sup&gt;13&lt;/sup&gt;C-PLFA. Lastly, scanning electron microscopy and nano scale secondary ion mass spectroscopy (NanoSIMS) analysis of free POM of both textures enabled qualitative insights directly at the biogeochemical interface of the microbial hot spot of decaying plant litter.&lt;/p&gt;&lt;p&gt;We were able to clearly demonstrate higher contents of litter-derived OM still residing as free POM in the loamy textured soil after the 95 day-incubation, while higher contents were found in occluded and MAOM in the sandy textured soil. This indicated that the overall litter decomposition was refrained in the finer-textured soil, whereas microbial alteration and allocation of litter-derived compounds was promoted in the coarser textured soil. This was further corroborated by higher respiration and higher amounts of respired litter-derived CO&lt;sub&gt;2&lt;/sub&gt;-C in the sandy soil. The PLFA analysis showed a coherent pattern between the textures, with similar community structures in all treatments and significant increases in microbial abundance in the top layers induced by litter addition. This increase was found most pronounced in fungal biomarkers, which was in line with the &lt;sup&gt;13&lt;/sup&gt;C-PLFA measurements revealing over 90% of fungal biomarkers to be of litter-origin (compared to 30-40% in the other microbial groups). The labelled PLFA profiles also confirmed the importance of fungi as a vector for litter-derived OM into deeper layers of the soil columns, with significantly higher litter-derived fungal markers also in center and bottom layers. The NanoSIMS measurements verified the high &lt;sup&gt;13&lt;/sup&gt;C enrichment in fungal hyphae and further revealed clay minerals embedded in enriched microbial-derived extracellular polymeric substances and intertwined with hyphae directly on top of the POM. Based on this comprehensive data, we highlight that regardless of the texture, plant litter in association with microbial-derived products represent a hot spot for soil structure formation by harbouring a core for aggregation and MAOM formation.&lt;/p&gt;

Soil Fungal Communities Investigated by Metabarcoding within Simulated Forensic Burial Contexts

Background One of the most debated questions in forensic science is the estimation of the post-mortem interval (PMI). Despite the large amount of research currently performed to improve the PMI estimation, there is still the need for additional improvements, particularly in cases of severely decomposed buried remains. A novel alternative to the morphological examination of the remains is the analysis of the soil microbial communities. Bacteria and fungi are ubiquitous and can be found in the soil and in/on the corpses, and their shifts in populational compositions present at different PMIs may reveal insights for PMI estimation. Despite it already having been revealed that bacteria might be good candidates for this type of analysis, there are knowledge gaps for this type of application when dealing with fungal communities. For this reason, we performed the metabarcoding analysis of the mycobiome present in the soil after prolonged decomposition times, from one- to six-months, targeting both the Internal Transcribed Spacer (ITS) 1 and 2, to elucidate which of the two was more suitable for this purpose. Results Our results showed a decrease in the fungal taxonomic richness associated with increasing PMIs and the presence of specific trends associated with specific PMIs, such as the increase of the Mortierellomycota taxa after four- and six-months post-mortem and of Ascomycota particularly after two months, and the decrease of Basidiomycota from the first to the last time point. We have found a limited amount of taxa specifically associated with the presence of the mammalian carcasses and not present in the control soil, showing that the overall the taxa which are contributing the most to the changes in the community originate from the soil and are not introduced by the carrion, extending the potential to perform comparisons with other experimental studies with different carrion species. Conclusions This study has been the first one conducted on gravesoil, and sets the baseline for additional studies, showing the potential to use fungal biomarkers in combination with bacterial ones to improve the accuracy of the PMI predictive model based on the shifts in the soil microbial communities.