Ten patients with PC (40%) were (borderline) resectable at baseline. Tissue was available from six patients . A median volume of 2.9 mL plasma (IQR 1.0 mL) and 0.7 mL PJ  was used for DNA isolation. PJ had a higher median cfDNA concentration (2.6 ng/μL (IQR 4.2)) than plasma (0.29 ng/μL (IQR 0.40)). A total of 41 unique somatic mutations were detected: 24 mutations in plasma , 19 in PJ , and 8 in tissue . The mutation detection rate (and the concordance with tissue) did not differ between plasma and PJ. In conclusion, while the concentration of cfDNA was indeed higher in PJ than in plasma, the mutation detection rate was not different. A few cancer-associated genetic variants were detected in both biomaterials. Further research is needed to increase the detection rate and assess the performance and suitability of plasma and PJ for PC (early) detection.Molecular profiling may enable earlier detection of pancreatic cancer (PC) in high-risk individuals undergoing surveillance and allow for personalization of treatment. We hypothesized that the detection rate of DNA mutations is higher in pancreatic juice (PJ) than in plasma due to its closer contact with the pancreatic ductal system, from which pancreatic cancer cells originate, and higher overall cell-free DNA (cfDNA) concentrations. In this study, we included patients with pathology-proven PC or intraductal papillary mucinous neoplasm (IPMN) with high-grade dysplasia (HGD) from two prospective clinical trials (KRASPanc and PACYFIC) for whom both PJ and plasma were available. We performed next-generation sequencing on PJ, plasma, and tissue samples and described the presence (and concordance) of mutations in these biomaterials. This study included 26 patients (25 PC and 1 IPMN with HGD), of which 7 were women (27%), with a median age of 71 years (IQR 12) and a median BMI of 23 kg/m Pancreatic cancer (PC) is a leading cause of cancer-related death due to asymptomatic progression leading to diagnosis at an unresectable stage in approximately 80% of patients ,2, whileCancers, including PC, arise as a consequence of accumulating gene mutations. Molecular profiling of tissue collected by fine-needle biopsy (FNB)—to assess these mutations—is less applicable for surveillance purposes, as it is invasive, relies on a visible mass, and is expected to obtain information from a single clone. Additionally, collection during endoscopic ultrasound (EUS) has been challenging due to low tumor cellularity and limited yield of tissue ,5. To daGene mutations may be investigated in circulating tumor DNA (ctDNA), which consists of short cell-free DNA fragments released into body fluids by cancer cells due to apoptosis, necrosis, and secretion. Multiple trials have aimed to diagnose PC (and its precursor lesions) based on plasma ctDNA, as it is non-invasively collected and expected to contain information from all present clones ,7. HowevPancreatic juice (PJ) may serve as an alternative biomarker source. A washout from the pancreas can be stimulated by secretin and collected from the duodenal lumen during endoscopy (without pancreatic duct cannulation or tissue sampling). As compared with FNB, PJ does not rely on a visible mass and is expected to contain information on the complete range of tumor clones ,12. As cWe hypothesized that the cfDNA concentration and mutation detection rate by next-generation sequencing (NGS) is higher in PJ than in blood plasma. This study aims to compare the detection rate of gene mutations in (cf) DNA from tissue, plasma, and PJ.n = 1) or PC (n = 25) were included. These individuals had a median age of 71 years (interquartile range (IQR) 12) and a median BMI of 23 kg/m2 (IQR 4), and 7 were women  stent in situ), epigastric pain , or weight loss . Eight patients had resectable, two had borderline-resectable, and 16 had  advanced diseases. The majority had a CA19.9 level > 37 kU/L  and did not undergo chemotherapy before plasma and PJ collection . The four individuals who had previously undergone chemotherapy received treatment with either FOLFIRINOX (#18 and #25 for 3 and 8 cycles) or gemcitabine combined with nab-paclitaxel (#16 and #26 for 4 cycles).In this study, 26 patients with histologically proven high-grade dysplasia  PJ was used for DNA isolation, which resulted in a median yield of 16 ng cfDNA from plasma ) and 1630 ng from PJ , p ≤ 0.001). As compared with plasma, PJ contained more long DNA fragments, as indicated by the long (247 bp) to short-fragment (115 bp) ratio (median 0.26 (IQR 0.07) vs. 0.42 (0.55), respectively, p = 0.03; p = 0.37; p = 0.003).A median volume of 2.9 mL (IQR 1.0 mL) plasma and 0.7 mL  was not associated to age, sex, BMI, previous chemotherapy, location of the solid mass, presence of a CBD stent, and resectability.p = 0.23). For the number of reads per panel and coverage, see For NGS, all isolated cfDNA (up to 25 ng) from plasma samples (range 4.7–25 ng) and 25 ng from PJ was used. For the Oncomine panel (#1–4), the number of reads ranged from 4.8 million to 7.0 million. For the Swift panel, the median number of used sequence reads was 2.8 million (IQR 1.4) for plasma and 2.6 million (IQR 0.9 million) for PJ , 19 in PJ , and 8 in tissue . At least one mutation was present in 17 (65%) plasma samples, 16 (61%) PJ samples, and 5 (83%) tissue samples (p = 0.22). The median number of mutations was 2 (IQR 1) for plasma, 1 for PJ (IQR 1), and 2 for tissue . The number of mutations per sample was not associated with the input cfDNA concentration, number of reads, Alu247/Alu115 ratio, age, sex, BMI, concentration of CA19.9, presence of DM, previous chemotherapy, resectability, CBD-stent in situ or the location of the solid mass : 5 plasma samples (19%), 9 PJ samples (35%), and 4 tissue samples ; no difference in the detection rate was found between PJ and plasma. As compared with tissue, plasma was concordant in one patient ; PJ was concordant in two patients . The concordance and detection rate were not related to resectability or the previous administration of chemotherapy. Concordance of KRAS mutations between PJ and plasma was seen in three patients : in 12 plasma samples (46%), 13 PJ samples (50%), and 4 tissue samples . For TP53, no concordance between tissue and plasma was seen, yet in two patients, concordance between PJ and plasma was seen (#13: R273H and #20: R248Q). The TP53 P72R homozygous germline variant (R72/R72) was present in 11 patients (5 (45%) had ≥1 TP53 mutation), and the TP53 P72R heterozygous germline variant (P72/R72) was present in 12 patients (12 (100%) had ≥1 TP53 mutation). Three patients had no P72R variant  had ≥1 TP53 mutation). As expected for a germline variant, the concordance between plasma and PJ was 100%.This study compares the detection rate of DNA mutations in PJ and plasma, which were (unexpectedly) found to be similar. While the concordance of the TP53 P72 variants was 100%, the concordance between biomaterials for variants with a lower allelic frequency was small. Additionally, both the total cfDNA concentration and the Alu247/Alu115 were higher in PJ than in plasma.BRCA2 mutated PC).cfDNA analyses in plasma and secretin-stimulated PJ can serve as non-invasive method for repetitive  sampling in a surveillance program. As (cancer) cells shed information to surrounding tissues and body fluids, it is expected that biomarkers are able to detect PC at an earlier stage. Additionally, in case of a suspicion of PC, obtaining a pancreatic biopsy is often challenging and requires multiple sampling efforts. Currently available biomarkers (such as CA19.9) have a high false-positive rate and are therefore not able to fulfill this need . AdditioWhile several studies have described ctDNA analyses in plasma or PJ for PC detection, we are the first to compare these two sources head to head. We hypothesized the superiority of PJ for the detection of PC (based on a higher concentration of DNA). Indeed, the current study showed a significantly higher cfDNA concentration as well as Alu247/Alu115 ratio in PJ than in plasma. This means that the cfDNA in PJ may potentially be contaminated with high concentrations of genomic DNA (as a result of cell decay during collection). Conversely, the higher Alu247/Alu115 ratio in PJ may be due to its close relation with PC and may be a measure of cell necrosis (rather than apoptosis), as necrosis produces longer cfDNA fragments ,15,16,17KRAS, our analysis showed a low KRAS detection rate in PJ  [KRAS detection rate when using secretin-stimulated PJ or pure PJ (collected by ampullary cannulation). However, no head-to-head comparison was performed in any of these studies.For erature)  as well TP53, this study shows a detection rate of 50% in PJ, which is higher than the detection rate in PJ previously described (43%) [TP53 detection rate was 46%. In patients >65 years (23 of 26 patients in this cohort), there is a potential for confounding plasma TP53 variants due to clonal hematopoiesis, but the low allelic frequency makes this unlikely [TP53 mutations is higher in patients with a germline heterozygous TP53 P72R (P72/R72) variant than in those with a homozygous variant (R72/R72). This is consistent with the study of De Souza et al. (2021) [TP53 genes in ovarian cancer cells harboring the P72 variant. Furthermore, van der Sijde et al. (2021) [For ed (43%) . This maunlikely . Our data et al. 21 [20,21. (2021)  showed tThis study has several limitations. Tissue (either resection or FNB specimen) was only available in six patients (for logistic reasons). Thus, we were unable to evaluate which of the observed mutations (in plasma or PJ) are actually reflective of tumor tissue. A few patients underwent previous chemotherapy, which may have caused a lower detection rate for these samples. To evaluate the performance of a test, a case-control design would be more valuable than the current design comparing detection rates. Another limitation of this study is the use of different kits for different samples. Based on our data, it is unclear which of the used kits performs better. At last, sample handling was different between plasma and PJ samples. Plasma was stabilized in EDTA anticoagulant and a cell preservative (CellSave)—proven to preserve the cfDNA quality and somatic variant detection ability in the serum for at least 96 h —and PJ wIn conclusion, this head-to-head comparison of plasma and PJ confirms a higher DNA concentration and Alu247/Alu115 ratio in PJ, yet it does not show the superiority of PJ over plasma in the detection rate of PC-related mutations. The exploratory nature of these results demands further research on sample handling  to increase the mutation rate in these samples and evaluate the potential applicability of PJ for molecular analysis. Furthermore, research with a case-control design is needed to compare the accuracy of mutations in PJ and plasma.Plasma, PJ, and tissue samples were prospectively collected at the Erasmus University Medical Center in Rotterdam as part of two clinical studies: 1. KRASPanc study (MEC-2018-038), concerning patients with (suspected) sporadic PC undergoing diagnostic EUS or fiducial placement for stereotactic radiotherapy; and 2. PACYFIC study (MEC-2014-021), involving individuals undergoing surveillance for suspected neoplastic pancreatic cysts. See Participants of these clinical studies were included for the present study based on the presence of (pathology-proven) HGD or PC and the availability of both plasma and PJ samples. Patients who had undergone radiotherapy or pancreatic resection prior to PJ collection were excluded. The availability of tissue samples was not an inclusion or exclusion criterion, and selection of tissue for NGS was based upon the availability of fresh-frozen tissue (from FNB or tissue) that had been performed during clinical workup. No formal sample size analysis was performed due to the explorative nature of this study.The institutional medical center ethical review board approved the studies, and included individuals gave written informed consent before enrolment. The studies were carried out according to the ethical principles for medical research involving human subjects from the World Medical Association Declaration of Helsinki.PJ collection was performed with a linear echoendoscope  by experienced endo-sonographers. After insertion of the tip of the echoendoscope into the D2 segment of the duodenum, secretion of PJ was stimulated by intravenous injection of human secretin . Suction through the endoscopic channel was applied immediately after secretin injection for eight minutes by positioning of the tip close to the ampullary orifice . Within Plasma samples were collected by venipuncture in CellSave tubes  on the same day as the PJ collection. After collection, centrifugation at 1600 rpm for 10 min was performed, and samples were aliquoted and stored at −80 °C until use. Before cfDNA isolation, samples were centrifuged at 16,000 rpm for 10 min, and DNA was isolated from the supernatant. Tissue samples were freshly frozen after resection  or FNB (#5) at the same day. Routine hematoxylin and eosin (H&E) stained sections from tissue samples were assessed for tumor cellularity by a pathologist, and areas enriched for tumor cells were identified and manually micro-dissected.For cfDNA isolation, an automatic bead-based Maxwell RSC cfDNA Plasma kit  was used according to the manufacturer’s instructions. The choice of a kit was based on previous results by our group . To quanTo prepare the tumor tissue samples for sequencing, the tissue was washed twice with PBS and subsequently treated with 550 µL lysis buffer and 20 µL protease overnight at 37–55 °C. RNase A (3 µL) was added and incubated for 15–60 min at 37 °C. Subsequently, a Chemagic MSM1 isolation robot  was used to isolate the DNA according to the manufacturer’s recommendations.CDKN2A, KEAP1, PTEN, STK11, TP53, and hotspots in other cancer genes  using the Oncomine Colon cfDNA Assay  using initial denaturation . Additionally, real-time qPCR was performed using Alu247 primers (forward: 5′-GTGGCTCACGCCTGTAATC-3′ and reverse: 5′-CAGGCTGGAGTGCAGTGG-3′) using the same PCR program as for Alu115. As cfDNA exhibits a narrow size distribution of ±167 bp, Alu115-qPCR results quantify the total amount of cfDNA, while the Alu247/Alu115 ratio illustrates the cfDNA integrity. DNA libraries were prepared by multiplex PCR using the Accel-Amplicon 57G Plus pan-cancer profiling panel , which covers 286 amplicons of 57 genes, amplified for 25 cycles in total (as per protocol), followed by the ligation of Illumina adaptors with sample specific indices. See http://www.cancerhotspots.org (accessed on January 2023). Mutations with allele frequencies higher than 49% were considered as homozygous or heterozygous germline mutations, not ctDNA mutations, and were excluded. The prevalence of TP53 P72R homozygosity and heterozygosity was noted, as it may modify the effect of TP53 hotspots mutants  [https://www.ncbi.nlm.nih.gov/clinvar/) and COSMIC (http://grch38-cancer.sanger.ac.uk/cosmic). Variants judged as benign were not tabulated. Recurrent mutations occurring in ≥10 samples were compared with prevalence in PC in the COSMIC database in case of an unusual high (100×) prevalence; PCR errors  and sequencing errors  were considered. These variants were only considered in case of AF > 0.5%. For instance, this applied to TP53 p.G245D, which was present in 25 of the 34 samples (74%) analyzed with the Accel-Amplicon 57G Plus pan-cancer profiling panel, yet present in only 9/2829 (0.3%) investigated patients in the COSMIC database. This also applied to SMAD4 p.R135* present in 17/34 (50%) samples (COSMIC: 7/2829) and PIK3CA p.E545A in 10/34 (29%) samples (COSMIC: 4/2273).Non-synonymous variants were considered as true mutations if these had a variant allele frequency (AF) > 0.1%, ≥5 mutated reads, and if they are ≥5 times described as somatic mutation in PC patients in the databases of COSMIC, OncoKB, and versial) ,25,26. Tp-values < 0.05 were considered significant.All statistical analyses were performed with SPSS ; figures were generated using GraphPad . Descriptive data were expressed as medians with IQR or percentages. Further statistical analyses were performed using a Wilcoxon paired-samples test or Spearman’s rank-order correlation for continuous variables.


We have recently identified a novel virus detected in alfalfa seed material. The virus was tentatively named alfalfa-associated potyvirus 1, as its genomic fragments bore similarities with potyvirids. In this study, we continued investigating this novel species, expanding information on its genomic features and biological characteristics.This research used a wide range of methodology to achieve end results: high throughput sequencing, bioinformatics tools, reverse transcription-polymerase chain reactions, differential diagnostics using indicator plants, virus purification, transmission electron microscopy, and others.Ipomovirus in the family Potyviridae. This assumption is based on the genome sequence and structure, phylogenetic relationships, and transmission electron microscopy investigations. We also demonstrated its mechanical transmission to the indicator plant Nicotiana benthamiana and to the natural host Medicago sativa, both of which developed characteristic symptoms therefore suggesting a pathogenic nature of the disease.In this study, we obtained a complete genome sequence of the virus and classified it as a tentative species in the new genus, most closely related to the members of the genus Potyviridae, of which alfalfa vein mottling virus is a tentative member.Consistent with symptomatology, the virus was renamed to alfalfa vein mottling virus. A name Alvemovirus was proposed for the new genus in the family The online version contains supplementary material available at 10.1186/s12985-023-02250-5. Medicago sativa L.), a major forage crop worldwide, greatly benefited from the latest advances in high throughput sequencing (HTS) technologies that enabled the completion of its genome assembly [Potyviridae that shared ~ 26–32% identity with a few members of the family. Therefore, the virus was provisionally named alfalfa-associated potyvirus 1 (AaPV1), [Potyviridae were established. The virus was further categorized as a novel species, tentatively related to the genus Ipomovirus and potentially representing a new genus in the family Potyviridae. Consistent with symptomatology in the natural host Medicago sativa L., the virus was designated as alfalfa vein mottling virus (AVMV), a representative member of a new taxon, provisionally named Alvemovirus.Research on alfalfa , . In the Five alfalfa plants (stems and leaves) were sampled from each of the four different fields, 10–15 acres in size, located in Yuma Country, Arizona, USA. Geographic coordinates of the alfalfa fields and the adjacent crops are shown in Table Five leaves were pooled from each of the 20 plants for RNA extraction. Total RNA was extracted using Promega Maxwell® RSC Plant RNA Kit  according to the manufacturer’s directions. cDNA libraries were prepared using Illumina TruSeq Stranded Total RNA with the Ribo-Zero Library Prep Kit  and RNA sequencing was performed by Psomagen  on a NovaSeq6000 S4 platform .https://www.ncbi.nlm.nih.gov/refseq/). The potential plant viral hits were searched once again using BLASTx against the full NCBI nr protein database. BBMap [A schematic representation of the bioinformatics pipeline used in this study is shown in Fig. e. BBMap  was usede. BBMap .Fig. 1BiN. benthamiana or with sterile RNAse-free water processed for cDNA preparation the same way as RNA extracted from the infected alfalfa plants. Three virus-specific sets of primers were designed based on the results of the HTS analysis: 1) LN1077/LN1078 ; 2) LN1079/LN1080 ; 3) LN1095/LN1096 . PCR products were either sequenced directly or cloned into the TOPO II vector  and sequenced.5’RACE was performed with SMARTer RACE 5’/3’ Kit  according to the manufacturer’s directions. Gene-specific primers for amplification were LN1074, 5’ GATTATCTGATTGGTTACCACAGAACTGGC 3’  and LN1115 5’ TGATCTCAAGGTGATTATCTGATTGGTTAC 3’ . Total RNA for RT-PCRs was extracted using TRIzol Reagent and reactions were performed using the SuperScript One-Step RT-PCR System or SuperScript™ III First-Strand Synthesis System following by PCR amplification with AmpliTaq Gold DNA Polymerase under conditions recommended by the manufacturer . Negative control reactions were performed with RNA obtained from uninfected Potyviridae. Sequences were aligned with Clustal W and the unrooted tree was built with RAxML-NG [Phylogenetic analysis was performed with polyproteins from selected members of the family RAxML-NG  using thN. benthamiana plants using sterile inoculating loops. Carborundum-dusted leaves of the three weeks-old seedlings of two alfalfa cultivars, cv. CUF 101 and cv. Maverick, were rub-inoculated with purified viral preparations using sterile inoculating loops.Symptomatic leaves from field alfalfa plants were homogenized in cold 20 mM potassium phosphate buffer, pH 7.0, using a sterile mortar and pestle. The resulting suspension was briefly centrifuged to precipitate plant debris and ten microliters of the supernatant were rubbed onto carborundum-dusted leaves of three-weeks old N. bentamiana leaves precisely as described in the protocol developed for Poinsettia mosaic virus [N. benthamiana leaves were homogenized in 0.07 M phosphate buffer (pH 7.2) containing 0.I % mercapto-acetic acid. Plant debris was removed by squeezing through cotton cloth, and the sap was mixed with n-butanol to 8% (v/v). After 30 min at 18°C, the mixture was used for one cycle of differential centrifugation  and the final pellet was resuspended in 0.03 M phosphate buffer [The virus was partially purified from 20 g of symptomatic ic virus . Brieflye buffer .For transmission electron microscopy (TEM), copper TEM grids were incubated on the drop of purified viral preparation for 2 min, rinsed with one milliliter of sterile water and stained with 1% phosphotungstic acid (PTA) solution. The grids were examined in a Hitachi H-7700 Electron Microscope at the Electron and Confocal Microscope Unit, Beltsville Agricultural Research Center.According to the results of HTS, eight out of 20 plants examined (40%) originating from three different alfalfa fields, were infected with the virus resembling AaPV1. These plants displayed a variety of virus-like symptoms including mottling, chlorosis, vein clearing, and bright yellow blotches . Among other hits were squash vein yellowing virus ; chili ringspot virus , and numerous species from different genera of the family Potyviridae.In a PSI-BLAST search, the top three hits for the viral polyprotein (excluding AaPV1 submissions) were: eggplant ipomovirus A ; the roymovirus, rose yellow mosaic virus ; and Potyviridae P1 protease domain (IPR002540); Helper component proteinase domain (PR001456); Protein P3 of potyviral polyprotein (IPR039560); Superfamilies 1 and 2 helicase ATP-binding type-1 domain (IPR014001); Superfamilies 1 and 2 helicase C-terminal domain ; Potyvirus NIa protease (NIa-pro) domain (IPR001730); Viral RNA-dependent RNA polymerase domain (IPR001205); and Potyvirus coat protein domain (IPR001592). The tentative genome structure of the virus and predicted cleavage sites, obtained by multiple alignment of 109 different potyvirids, are shown in Fig. The InterPro tool for functional analysis of proteins , predict1-2 A6-7 motif preceding overlapping PIPO ORF characteristic for Potyviridae and located within the P3 cistron [7 motif, which is embedded in the overlapping ORF, presumably  starting at the position 3122 nt (+ 3 ORF relative to the polyprotein) and followed by 63 codons with a termination codon TGA at pos. 3311–3313.The virus does not appear to have a highly conserved G cistron , InsteadPotyviridae, clustered the virus into a distinct outgroup, branching from the genus Ipomovirus , we attempted mechanical transmission of the virus to N. benthamiana, a common indicator host for diagnosis of many plant viruses [N. benthamiana plants mechanically inoculated with sap produced from infected alfalfa leaves, developed distinct symptoms two–three weeks post inoculation. The resulting symptoms could be visually characterized as chlorosis, mottling, and chlorotic lesions on non-inoculated leaves. The infected plants were also stunted compared to healthy control plants  can provide reliable information on particle dimensions and morphology, based on which a virus can be placed to a particular taxonomic group . TEM exaAmong several plants of two alfalfa cultivars inoculated with purified viral preparations, only a single plant of cv. CUF 101 developed obvious symptoms ~ 20 days post mechanical inoculation. Symptoms consisted of mottling and vein yellowing Fig. A. The syMedicago sativa L.) and belonging to the family Potyviridae. Genomic fragments of the same virus were previously found in mature alfalfa seeds [We report here the identification and characterization of a new virus infecting alfalfa , it is possible that AVMV is also whitefly-transmitted and could infect other crops growing in the vicinity. Therefore, further studies will examine incidence of AVMV in additional regional crop and/or weed species and the potential for AVMV transmission by B. tabaci. Since all alfalfa samples used in this study were collected within 100 m of the melon fields in an area with exceptionally high populations of the whitefly, B. tabaci MEAM1, (Table Viruses of the genus Medicago sativa L.), a major forage crop worldwide. The virus was identified as a member of the large and economically important family Potyviridae, in which it tentatively belongs to the new genus designated as Alvemovirus.This work reports the discovery and characterization of a novel plant viral pathogen naturally infecting alfalfa (Additional file 1 Table S1. Different viral contigs generated from each of the eight plant samples infected with the virus


Host density is one of the main factors affecting the infective capacity of viruses. When host density is low, it is more difficult for the virus to find a susceptible cell, which increases its probability of being damaged by the physicochemical agents of the environment. Nevertheless, viruses can adapt to variations in host density through different strategies that depend on the particular characteristics of the life cycle of each virus. In a previous work, using the bacteriophage Qβ as an experimental model, we found that when bacterial density was lower than optimal the virus increased its capacity to penetrate into the bacteria through a mutation in the minor capsid protein (A1) that is not described to interact with the cell receptor.Here we show that the adaptive pathway followed by Qβ in the face of similar variations in host density depends on environmental temperature. When the value for this parameter is lower than optimal (30°C), the mutation selected is the same as at the optimal temperature (37°C). However, when temperature increases to 43°C, the mutation selected is located in a different protein (A2), which is involved both in the interaction with the cell receptor and in the process of viral progeny release. The new mutation increases the entry of the phage into the bacteria at the three temperatures assayed. However, it also considerably increases the latent period at 30 and 37°C, which is probably the reason why it is not selected at these temperatures.The conclusion is that the adaptive strategies followed by bacteriophage Qβ, and probably other viruses, in the face of variations in host density depend not only on their advantages at this selective pressure, but also on the fitness costs that particular mutations may present in function of the rest of environmental parameters that influence viral replication and stability. The infection cycle of any virus can be divided into two phases, an intracellular one, corresponding to the period of replication inside the cell, and an extracellular one, comprising the time between infections. In the extracellular phase, viruses behave as inert entities –the virions– that are exposed to the physicochemical conditions of the environment, which can damage the virus particles and compromise the ability to initiate new infections. The time that a virus remains in the extracellular environment is strongly conditioned by virus and host concentration. Due to mass action kinetics, host concentration is the most relevant factor influencing the number of infections that can be initiated from a viral population of a given size . VirusesSometimes, improving one of the parameters described above implies worsening others, that is, it has a fitness cost . An examEscherichia coli using as receptor the conjugative F pilus. It is a member of the Leviviridae family (genus Allolevivirus)  and the virus genomic RNA penetrates inside the central channel that traverse the plasma membrane at the basis of the pilus and is driven into the host cytosol  . It has vivirus) . It consvivirus)  that is vivirus) . Around  cytosol . Due to  cytosol , a simil cytosol .In a previous work, we studied the adaptation of bacteriophage Qβ to replicate in the presence of different bacterial densities at the optimal replication temperature for the virus (37°C) . A fractIn the experiments presented in this work, we have studied the effect of varying cell density at the same time that another essential parameter for virus replication, temperature, is also modified. Temperature largely influences the tertiary structure of proteins. Therefore, it is to be expected that all processes involving interaction between molecules and structures (for instance between phage and bacteria components) or enzymatic catalysis are affected by variations in this parameter. The impact of temperature changes on Qβ replication and evolution has been previously studied in depth in our laboratory, although always at the same bacterial density that we use as a standard. While the decrease in temperature (from 37 to 30°C) does not strongly decrease viral titers, the increase (from 37 to 43°C) produces drastic reductions in the virus yield . NeverthThe new results we have obtained show that, when bacteria availability is reduced, bacteriophage Qβ selects a common adaptive strategy both at 30 and 43°C, which is based in the improvement of its entry into bacteria. However, while at 30°C adaptation is achieved through the same mutation in the A1 protein that was selected at 37°C, at 43°C it does so through a different mutation located in the A2 protein (V256A), which has strong fitness costs at lower temperatures. It appears, therefore, that adaptation of bacteriophage Qβ to low host availability involves different mutational pathways depending on the balance between fitness advantages and costs at each replication temperature.Escherichia coli DH5-α, a strain that permits virus expression, although it cannot be infected because it lacks the virus receptor. The supernatant of an overnight culture, obtained from a transformed colony, was used to infect E. coli, strain Hfr (6 plaque forming units (pfu) were used to infect an E. coli Hfr culture under standard conditions  for 2 h. The supernatant of this culture was used as the ancestor of all the evolutionary lineages analyzed in this work. It was denoted QβAnc and its consensus sequence showed no mutations relative to the Qβ cDNA cloned in pBR322. The virus QβAnc is the same described in our previous work concerning Qβ adaptation to low host density . Infections in liquid medium were carried out using fresh log-phase E. coli cultures with an OD600 of 0.8 that were infected with the amount of pfu indicated in each experiment. Cultures were incubated at the indicated temperature for 2 h with good aeration (250 rpm). To estimate the total virus yield, cultures were treated either with chloroform  or with egg white lysozyme . Virus supernatants were harvested upon centrifugation at 13000 × g and maintained at 4°C for short-term use (less than 15 days) or at −80°C for long-term storage. Virus titers were determined by plaque assay and expressed as the number of pfu per ml of the phage suspension.Qβ was propagated in Anc was used to initiate 8 replicate evolutionary lineages differing in the bacterial density  per ml.1 The culture was serially diluted in NB medium , and 0.5 ml of either the undiluted culture or the corresponding dilution were placed in 10 ml tubes containing 400 μL of NB. Infections were initiated with 107 pfu in 100 μL of phage buffer . After 2 h of incubation under standard conditions either at 30 or 43°C, the virus supernatants were collected upon treatment with chloroform, and a fraction of the phage suspension  was used to infect fresh E. coli cultures prepared as described above. Evolutionary lineages were denoted Qβ (3 × 108)30°C, Qβ (3 × 108)43°C, Qβ (3 × 107)30°C, Qβ (3 × 107)43 ^° C, Qβ (3 × 106)30°C, and Qβ (3 × 106)43°C to indicate the bacterial density (in brackets) and the temperature used in the experiment. Lineages propagated at the bacterial density of 3 × 105 cfu/ml were extinguished before transfer 16 and were not used for further experiments. When necessary, the numbers 1 and 2 were used to distinguish the two replicas performed for each condition.The virus Qβ density . PropagaA negative control in which undiluted bacteria were incubated in culture medium in the absence of virus was set at each transfer. This control was processed and plated exactly the same as the experimental samples. When lysis plaques appeared, the corresponding transfer was discarded and repeated again.U830C), and C2011A (virus QβC2011A). The replication temperatures and the bacterial densities used are indicated in the text and in the legend of the corresponding figures.Additional evolution experiments using a similar protocol to that described above were performed with single mutant viruses containing mutation U830C  for 30 min at 37°C with shaking (850 rpm in thermoblock). Lysozyme was used instead of chloroform because of its higher efficiency to lysate cells, demonstrated in several lysis assays carried out in our lab (data not shown).The virus yield obtained in replication assays carried out in liquid medium was used as a measure of the virus replicative ability. Triplicate liquid cultures containing the indicated bacterial density were inoculated with 10U830C) or C2011A (virus QβC2011A). Mutagenesis was carried out using the QuickChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies) with the primers 5′GACAATCTGTACCCTGCCGCTGCTTACTTTAAACTGAAA3′ (for QβU830C) and 5′TGGGATTCTCGGCTTAGTTATAACACGT TCCGCGG3′ (for QβC2011A), together with their respective complementary containing the mutations to introduce in the virus genome. The procedures to build and isolate the site-directed mutants were the same as previously described for other Qβ mutants . Plaques were incubated overnight at 37°C. Images of the Petri dishes were taken with ChemiDoc MP Imaging System (Bio-Rad) using a white sample tray and “Coomasie Blue” mode. Images were analyzed with Image Lab Software (Bio-Rad) (RRID:SCR_014210), using the tool “Volume Tool-Round” to manually select 70 lysis plaques of each virus whose areas were calculated. We used the Mann-Whitney test to assess the statistical significance of the differences between different sets of data.Areas of the lysis plaques formed by the viruses Qβ8 cfu/ml) and 105 pfu of the indicated virus, were incubated at either 30, 37, or 43°C with low shaking (75 rpm) for 0, 5, 10, 15, and 20 min. At each time, 100 μL of EDTA 100 mM were added to stop virus entry. A control experiment showed that incubation of Qβ with this EDTA concentration completely inhibited its entry into E. coli, which agrees with previous results obtained for other phages , N is the number of bacteria in the sample (3 × 108 cfu), and t is the incubation time. We defined the parameter k (expressed in ml/min/cell), corresponding to c/N, as the constant of formation of infectious centers at the bacteria density assayed. Fittings were performed using the function NonLinearFit of Mathematica 9.0 (Wolfram Research). Viruses whose k-values were compared were always assayed in the same experiment, using the same cell preparation. Differences were considered statistically significant when the value obtained for a particular virus was outside the confidence interval of the one to which it was compared.where t-test.Additional experiments were performed in the same way but with a fixed incubation time (10 min) and using different bacterial concentration (indicated in the corresponding figure). The statistical significance of the differences between the number of infectious centers obtained in different sets of data was assayed by means of the Student’s 8 bacteria and 106 pfu of the viruses QβAnc, QβU830C, or QβC2011A were incubated for 5 min (curves performed at 30 and 37°C) or 10 min (curves performed at 43°C) in NB medium and 75 rpm. The reason for incubating longer at 43°C was to allow the entry of a greater amount of virus to mitigate the low replication yield at this temperature. In all cases, virus entry was stopped by a 10000-fold dilution of the cultures. Diluted cultures were incubated at the temperature assayed in a static bath, and only mixed by inversion right before taking the samples, to avoid additional encounters between cells and viruses. At different times, 250 μL aliquots were removed and centrifuged to obtain the virus supernatants that were titrated. The duration of the latent period was calculated as the intercept between the regression line of the natural logarithm of the virus titers vs. time during the exponential rise period and the regression line for the points corresponding to the pre-rise period.Duplicate 1 ml liquid cultures containing 3 × 108 bacteria and 106 pfu of the virus indicated were incubated for 10 min at either 30, 37, or 43°C in NB medium and 75 rpm to allow virus entry into bacteria. After this time, a 0.3 ml aliquot was removed to determine the number of infectious centers as described above (see section “2.6. Determination of virus entry into bacteria”). Another 0.3 ml were diluted 100000-fold (for the assays carried out at 30 and 37°C) or 10000-fold , and incubated at the same temperature used for virus entry with shaking (250 rpm). The incubation times were 75, 55, and 75 min for QβAnc and QβC2011A at 30, 37, and 43°C, respectively, and 90, 80, and 75 min for QβU830C at 30, 37, and 43°C, respectively. The times were chosen so that each virus would have reached the plateau as shown in the one step growth curves. After these times, the virus supernatants were collected and titrated to estimate the amount of extracellular virus. The burst size was calculated by dividing the virus titers  by the number of infectious centers determined in the aliquot removed after the initial 10 min allowed for virus entry.Triplicate 1 ml liquid cultures containing 3 × 10E. coli Hfr into a 50 ml flask. The culture was treated with 500 μL of chloroform at 25°C, 250 rpm for 20 min. To completely break the cells, the flask was vortexed at maximum speed for 5 extra minutes. Finally, lysates were centrifuged at 25°C, 12000 rpm for 10 min. A 300 μL fraction of the supernatant was plated on an NB plate to check that there were no live bacteria remaining that could allow virus replication. Triplicates containing 1 ml of lysate supernatant were incubated with 3 × 105 pfu for 16 h at 30, 37, or 43°C. Controls for each temperature were prepared the same way, but using NB instead of lysate supernatant. Test samples and controls were titrated by plaque assay.To study the virus interaction with cellular debris, cellular lysates were prepared by transferring 10 ml of a stationary culture of 2 Mutations relative to the sequence of the virus QβAnc were identified using the same software.Viral RNA was prepared following standard procedures to determine the consensus sequence either from biological clones or from complex virus populations. RNAs were used for cDNA synthesis with the avian myeloblastosis virus reverse transcriptase (Promega), followed by PCR amplification using Expand high-fidelity DNA polymerase (Roche). The pairs of oligonucleotide primers used for RT-PCR were the following: P1 forward (5′CTTTAGGGGGTCACCTCACAC3′) with P1 reverse (5′GGATGGGTCACAAGAACCGT3′) to amplify from nucleotide position 10 to 1595, P2 forward (5′GACGT GACATCCGGCTCAAA3′) with P2 reverse (5′CAACGGACGGAACATCTCCT3′) to amplify from nucleotide position 1109 to 2787 and P3 forward (5′GTGCCATACCGTTTGACT3′) with P3 reverse (5′GATCCCCCTCTCACTCGT3′) to amplify from nucleotide position 2254 to 4195. PCR products were column purified (Qiagen) and subjected to standard Sanger sequencing using Big Dye Chemistry with an automated sequencer . Sequences were assembled and aligned with Geneious Pro v4.8.5.t-test (Function T-Test).All statistical analyses were performed with the program Mathematica 9.0 (Wolfram Research). When calculating the statistical significance of the differences between two series of data, the Location-Test function was used to choose the most appropriate test for the comparison, which in all cases, except for the comparison of the size of the lysis plaques produced by different viruses, was the 8 cfu/ml. To analyze the effect of temperature on phage replication as a function of the host density, the phage was propagated for 16 transfers at either 30 or 43°C. For each temperature, we tested the following concentrations of bacteria: 3 × 108, 3 × 107, 3 × 106, and 3 × 105 cfu/ml, performing two replicas for each  as a function of temperature is shown in In our previous publication , we founfor each . Since aAnc), were used to determine whether the optimal bacterial density for Qβ replication depended on temperature. At 30°C, we observed that the curve flattened between 3 × 107 and 3 × 108 cfu/ml, and at 43°C the maximum virus titer was obtained at 3 × 107 cfu/ml . In that case, the virus was extinguished at transfers 9 and 10 for the replicas performed at 30°C, and at transfer 7 for those performed at 43°C. As it happened during the propagation of Qβ at 37°C at lower-than-optimal bacterial densities, the evolutionary lineages (with the only exception of the two replicas propagated at 43°C at 3 × 108 cfu/ml) became progressively enriched in viruses that gave rise to lysis plaques with smaller-than-usual size. In the following sections we will analyze this character quantitatively.The results obtained in the first transfer, which in all cases was initiated from the same virus sample . The results obtained .We then determined whether the populations obtained at transfer 16 had increased their replicative ability with respect to the ancestor. To ensure that viral production was not saturated during the assay, this was performed with 10obtained  showed tTo determine the genetic changes responsible for adaptation to the assayed conditions, we determined the consensus sequences of all evolutionary lineages obtained at transfer 16 . The mos8 cfu/ml, mutation U830C (V256A in the A2 protein) was present. In addition, other mutations, some of which had previously been identified in other experiments of Qβ adaptation to high temperature and standard bacterial density, were also detected (5 cfu/ml. It is interesting that mutation A1088G (D342G in the A2 protein), which was always selected in our lab when Qβ was adapted to 43°C using bacterial densities around 3 × 108 cfu/ml, was not selected when the amount of available bacteria was lower.The results obtained at 43°C showed interesting differences with those observed at 30 and 37°C. First, mutation C2011A was not selected in any lineage. In contrast, in all those propagated at bacterial densities below 3 × 10detected . The preU830C) or C2011A (virus QβC2011A). We determined the virus titers obtained in a replication assay carried out with the single mutants at both selective and non-selective temperatures at all the bacteria concentrations compatible with the preservation of the virus population for the 16 transfers of the evolution experiment  showed that mutation U830C only increased significantly the virus titers at 43°C at 3 × 107 cfu/ml (8 cfu/ml) or the difference was non-significant (3 × 106 cfu/ml), suggesting that the presence of this single mutation is not sufficient for the virus to adapt to both selective pressures, high temperature and low host density, simultaneously. Mutation C2011A increased the replicative ability with respect to the virus lacking the mutation at all bacteria densities assayed at 30°C.The virus yields obtained at selective temperatures , both mutations always rendered lower virus yields than the ancestor  . It is remarkable that in all assays carried out to determine the replicative ability of the mutant QβU830C  for the virus QβAnc at 30, 37, and 43°C. We observed that this virus generated infectious centers more rapidly at 43°C than at 37°C, and the lowest value was obtained at 30°C  was probably due to the poorer fit of the experimental points to the function used, resulting in wider confidence intervals.Then, we compared the value of the constants obtained for the virus Qβand 43°C . Each coAnc, QβU830C, and QβC2011A were incubated for a fixed time (10 min) with different bacterial densities, after which the number of infectious centers formed was determined. The results obtained  followed by a sharp decline until almost the total elimination of viral infectivity at 24 h. In contrast to this, different amounts of virus incubated for 24 h in NB medium at 43°C did not show any significant decrease in their titers. The result suggests that Qβ loses infectivity faster when it is replicating in a medium with bacteria than in cell-free NB medium.Another feature influencing virus fitness is the time that infectivity can be preserved in the extracellular environment in the period between infections. Previous assays carried out with the virus Qβ5pfu of the ancestral virus or the mutants QβU830C and QβC2011A for 16 h at 30, 37, and 43°C, after which the virus infectivity in each sample was assayed. The results , and incubated it with about 3 × 10 results  showed tU830C at 37°C (8 cfu/ml) or low (3 × 105 cfu/ml). In both conditions, the virus experienced an initial increase in its titers, which was greater at high bacterial density, and remained fairly constant during the rest of transfers. The consensus sequences showed the loss of mutation U830C in the two replicas carried out at high bacterial density and the permanence of the mutation when the bacterial density was low , using a high (3 × 108 cfu/ml) or a low (3 × 106 cfu/ml) bacterial density  that remained constant with some fluctuations throughout the experiment. Determination of the consensus sequences at transfer number 10 showed that, at high bacterial density, mutation C2011A was lost in both replicas, whereas at low bacteria density, the mutation could be preserved, although it was always accompanied by U830C  . In all 7 cfu/ml. From this point on, the increases were low (30°C) or turned into declines (43°C)  and the other one higher (43°C). It is noteworthy that, in both cases, the curves of viral yield as a function of bacterial density approached a plateau at about 3 × 10s (43°C) . In this5 cfu/ml. Under this condition, the virus was extinguished in both replicas carried out either at 30 or 43°C, probably due to the low viral production when two selective pressures  are operating together. As it happened in the experiment carried out at 37°C, another observable phenotypic feature was that in all lineages evolved at 30 and 43°C [with the only exception of the two replicas of Qβ (3 × 108)43°C] as the number of transfers increased the lysis plaques became smaller than usual. There are several theoretical and experimental studies that attempt to relate the changes in the parameters defining the viral infective cycle with the size of the lysis plaques  selected mutation C2011A in the A1 protein, similarly to Qβ evolved at 37°C and bacterial densities lower than 3 × 108 cfu/ml  at high and low bacterial densities could be maintained at this temperature (5 cfu/ml) (C2011A propagated at 43°C (non-selective temperature) at low host density showed an increase in the virus titers as the number of transfers increased  . A similncreased . Mutationcreased . SequencThe most important conclusion that can be drawn from this work is that adaptation of Qβ to reduced host availability can be addressed by at least two different mutations that increase virus entry into bacteria. The choice of one or other depends on environmental parameters such as temperature that may affect the strength of the virus-cell interaction, the ease of internalizing the virus genome or the ability to generate an infectious progeny. The balance between the advantages and the fitness costs of each mutation under the particular conditions of virus replication is what decides if it is selected or not.The original contributions presented in this study are included in the article/EL designed the study and wrote the manuscript. ML-C, AR-M, and ELl performed the experiments. EL and ML-C analyzed the data. All authors interpreted the results and reviewed the manuscript.


Triple-negative breast cancer (TNBC) is an aggressive and therapy-resistant form of breast cancer with a significant economic burden on patients and healthcare systems. Therefore, we completed a systematic review to classify and synthesize the literature on the direct and indirect costs of TNBC.Databases including ISI Web of Science, Scopus, PubMed, and Google Scholar were searched for all related articles assessing the economic burden of TNBC from 2010 until December 2022. The quality and eligibility assessments were done accordingly. We adjusted all costs to January 2023 $US.From 881 records, 15 studies were eligible. We found that studies are widely disparate in the timetable, study design, patient populations, and cost components assessed. The annual per-patient direct costs of metastatic TNBC (mTNBC) were about $24,288 to $316,800. For early TNCB patients (eTNBC) this was about $21,120 to $105,600. Cancer management anticancer therapy costs account for the majority of direct costs. Along with an increase in cancer stage and line of therapy, healthcare costs were increased. Moreover, the indirect costs of patients with mTNBC and eTNBC were about $1060.875 and about $186,535 for each patient respectively.The results showed that the direct and indirect costs of TNBC, mainly those of mTNBC, were substantial, suggesting attention to medical progress in cancer prognosis and therapy approaches.The online version contains supplementary material available at 10.1186/s12962-023-00503-2. Cancer, the most common disease, and the second leading cause of mortality globally refer to several diseases characterized by the progress of unusual cells that grow uncontrollably . Breast In the present study, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendation to identify, select, and critically evaluate all relevant research published between the years of January 2010 and January 2023 .In this systematic literature review, we searched articles from established literature search electronic databases like, PubMed, ISI Web of Science, Scopus, and Google Scholar from January 2010 and January 2023  was used to identify and remove potential duplicate articles. Data were extracted from relevant studies, economic evaluations, and clinical trials. For the direct and indirect costs of patients with TNBC, data were extracted from relevant articles. Direct costs are costs that are related to patient care directly, for example: drugs, nursing services, diagnostic imaging, medical supplies, and rehabilitation. Indirect costs - are costs that are not directly attributable to patient care. For instance: reduction of work productivity or loss of job, information technology, general administration, human resources, health records, physical plant and maintenance, and other local facilities. The eligibility criteria inclusion was presented in Fig. The authors independently reviewed the titles and abstracts of the articles and evaluated full texts for eligibility. Irrelevant studies, duplicated articles, and studies that did not cover the inclusion criteria were discarded. Using a conventional data abstraction process, the authors contributed to preparing the following data from each included article: authors and year of publication, population, setting, country, interventions, age, indirect costs, direct costs, and study design. In the next stage of the selection process, for the risk of bias, extracted data were additionally assessed by Dr Sadeq Rezaie independently .The qualitative investigation was passed by two authors (SR and MB) using a checklist. The qualitative investigation was checked by the authors SR. The following points were checked: study design and analysis, economic burdens, scope, type of costs, full text, and availability of the results.Because of the diversity in time and place of studies, we adjusted all costs to 2023 (January) USA dollars ($US) for simplifying comparisons between studies as described previously . In artiThe search and assortment procedure to identify relevant studies, which investigated the economic burden of TNBC, was provided as a flow diagram Fig. . As showThe 15 articles published between 2010 and 2022 assessed TNBC-related direct medical costs and indirect costs  . A work ,826 . A For indirect costs, a work showed that the mean indirect costs were $186,535 for each mTNBC patient after 5 years of follow-up in Spain   and medical decisions  for patients and healthcare payers. These studies may cause an advance in cancer prognosis and therapy methods. In addition, the majority of the studies have been accompanied in high income countries, strategy creators of the healthcare in middle and low income nations need urgencies investigation of such situations.Below is the link to the electronic supplementary material.Supplementary Material 1


Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health. Tisza et al. carry out a sequencing-based analysis of wastewater samples from major cities, to detect and quantify hundreds of distinct pathogenic viruses, finding striking correlations between virus abundance and local clinical cases. During the COVID-19 pandemic, the WBE field underwent significant reinvestment6, wherein PCR-based detection of SARS-CoV-2 was used as a proxy for community infection levels, and amplicon sequencing facilitated the resolution of SARS-CoV-2 variants well before clinical detection9. As such, viral WBE, while initially used for environmental poliovirus surveillance nearly a century ago10, has now been leveraged to track influenza virus11, respiratory syncytial virus12, enterovirus D6813, and monkeypox virus15 using modern PCR-based methods. Although delivering high sensitivity and specificity, these methods are limited as they cannot provide a comprehensive assessment of human virus levels, community diversity, and variant compositions in a heterogeneous sample.Wastewater-based epidemiology (WBE) refers to the specific detection and tracking of substances16, targeted amplification9, and/or hybrid capture methods20 to enrich for rare viral sequences amongst the backdrop of what is mostly nucleic acid from bacteria and mammalian hosts. These studies have seen mixed success, not been applied at scale, and the extent to which the levels of virus sequences corresponded to community infection levels is unclear. In any case, even the most prevalent wastewater viruses, e.g., human astroviruses and rotaviruses, comprise a very small fraction of the total biomatter in wastewater, especially compared to other microorganisms, such as bacteria22.Recent approaches have investigated the use of virus-like particle enrichmentClinical reporting of infectious diseases is extremely valuable for understanding potential sources of outbreaks and disease burden on those with co-morbidities and certain population demographics, but it is constrained by resources, changes in human behavior, and trends in clinical practice. We demonstrate that WBE employing virome sequencing provides insights into aggregate community loads of specific pathogens, viral evolution, dynamics between different viral species or variants, and is presumably agnostic to clinical reporting biases. Specifically, we apply a probe-based capture method accounting for thousands of human and animal viruses followed by deep sequencing to wastewater samples from two major cities whose combined populations reach nearly 3 million people. We reveal the dynamics of the human virome in space and time from hundreds of pathogenic viruses, correlate some of this activity to established detection platforms and clinical data sets, and identify widespread allelic variants of specific viruses for evolutionary tracking.23, composite 24-h wastewater influent was collected from six treatment plants in Houston, Texas, USA and four plants El Paso, Texas, USA from May 2022 through February 2023  are directed against a panel of 3153 different human and animal virus genomes. As part of an initiative from the Texas Epidemic Public Health Institute023 Fig. . Wastewa24, we first sequenced and examined viral read numbers from unenriched samples. Low proportions of viral reads were derived from these unenriched samples , with 0 to 1 total mammalian viruses detected. In contrast, utilizing the TWIST Comprehensive Viral Research Panel probes on the same extractions, a 3,374-fold enrichment in the proportion of virus reads was observed .Read mapping-based virus detection and abundance measurement was conducted using EsViritu, a bioinformatics tool we developed for this purpose Fig. . EsViritApplying these methods to 363 longitudinal wastewater samples, we detected 28 viral families, 77 genera, 191 species, and 465 distinct virus strains in total Fig. , with a R = 0.975  virions to real wastewater samples (samples were previously determined to have no detectable RSV). Based on a stepwise dilution series, we could accurately detect and quantify RSV from a spike-in of 51 genome copies to 4 million genome copies with a Pearson correlation of at least 975 Fig. .25. Using the reads per kilobase of transcript per million filtered reads (RPKMF) as a proxy for relative virus levels in a given sample, there was a positive correlation between case data and positivity rate for SARS-CoV-2 summer and winter waves and the wastewater signal in Houston  and case data from El Paso . This finding is strengthened by the fact that a second orthogonal technique to measure SARS-CoV-2 levels in wastewater  was also closely correlated with the RPKMF  and El Paso (R = 0.84).Having established a capture-based approach that offers the prospect of a comprehensive virome analysis of complex wastewater samples, we next asked whether signals generated from sequencing data mirror trends observed from publicly available clinical datasets. Case data from select viral pathogens, namely SARS-CoV-2, influenza virus, and monkeypox virus, were obtained for Houston and, when available El Paso, from local or state government sources. We started first with SARS-CoV-2, as wastewater levels have previously been correlated with case dataKMF Fig.  for bothR = 0.9). Influenza variants H3N2 and H1N1 were also resolved in our data, concordant with clinical subtyping of this flu season in Texas . Once more, the virome sequencing data was highly correlated with qPCR measurements from the same samples . Finally, a Monkeypox (Mpox) outbreak occurred in the summer of 2022 in several U.S. cities. Rather strikingly, monkeypox virus was detected numerous times at low abundance in Houston wastewater samples  in our virome dataset, even though only 1,050 cases were reported in the entire Houston area between July and November 2022. Meanwhile, no detection events of monkeypox virus were recorded from El Paso wastewater samples, consistent with only 10 total reported clinical cases in this metro area.Similarly, Influenza A Virus abundance in the virome sequencing data was highly concordant with reporting of “Weekly Percentage of Visits with Discharge Diagnosed Influenza” in the Houston area Fig. , R = 0.9Encouraging from a detection and possibly public health standpoint, 11 categories of “major” viral pathogens were routinely detected and could be tracked over the sampling period Fig. , includiWe wished to understand how the human wastewater virome changed over space and time. Important variables in the structure of virome communities were realized by generating t-distributed stochastic neighbor embedding (t-SNE) plots from the virus abundance data of each sample. There was a stark separation of the samples by the city of collection and date of collection Fig. . Virus sTo assess community dynamics over time, all samples from each site were compared to each other using the Bray-Curtis dissimilarity statistic Fig. . In geneA handful of viruses had high or complete genome coverage across many wastewater samples and were therefore suitable for variant analysis. Although a single lineage seemed to dominate the sample read abundance for some virus strains, many samples had a mix of two or more lineages. Therefore, allelic variants were measured by the frequency of non-synonymous mutations compared to the reference genome. We focused on three examples.26, was the virus contained at high genome coverage in the most samples in our dataset. The variant landscape of Astrovirus MLB1 was largely dictated by the city-of-origin of the sample  the ability of a hybrid-capture probe approach that is designed against over 3,000 human and animal viruses to, when combined with deep sequencing, significantly enrich viral detection ; (ii) the approach’s suitability as a record of aggregate community infection levels for several key viruses of concern, including SARS-CoV-2, influenza virus, enterovirus D68, noroviruses, rotaviruses, monkeypox virus, respiratory syncytial virus and many others; (iii) the clear correlation of genome-specific sequencing reads to clinical data for SARS-CoV-2, influenza virus, and monkeypox virus; (iv) dynamics of the virome that change across space and time; and finally (v) the variant tracking of viruses with high genome coverage and prevalence.Although this approach already offers a suitable estimation of relative virus levels, genomes of important pathogens such as SARS-CoV-2, influenza virus, and monkeypox virus were typically not sequenced at high enough coverage to assess allele and variant frequency. This was probably because these viruses do not typically carry high viral loads in the gastrointestinal or urinary tract and are not shed into wastewater in high numbers. Therefore, continued development of the enrichment methodology as well as increased sequencing depth should be considered to improve genome coverage.This comprehensive hybrid-capture methodology also holds promise for near real-time as well as retrospective assessments as it promises to detect virus genomes up to 15% different from known references. Also, additional probes can be logically designed and added to the existing reagent to capture highly divergent pathogens. In this way, we believe that, amongst other uses, this type of wastewater monitoring promises to be a useful, cheap, and scalable “smoke alarm” for populations under threat from dangerous pathogens.Figure 9, rather than geography. It is not clear whether this pattern observed for highly transmissible SARS-CoV-2 applies to other, less transmissible human viruses. Indeed, the data presented here for three highly abundant viruses suggests that this may not be the case .The literature suggests that, while some SARS-CoV-2 variants were largely limited to certain geographies, major lineages  swept across the globe and were primarily separated by time30. JC Polyomavirus is known to establish long asymptomatic infections in the large majority of people, probably being transmitted within households sporadically29. Astrovirus variants may be introduced to an immune-naive population or city and spread outbreak-by-outbreak over the course of months, whereas different JC polyomavirus lineages acquired by different people over many years could be shed simultaneously, blurring allelic patterns seen with other viruses. It is tantalizing to consider that such an approach may help us understand the underlying infection etiology of these and related viruses as it pertains to entire population transmission and dynamics.The geographic partitioning between, for instance, allelic variants of astrovirus MLB1 but not JC polyomavirus Fig.  may be dThe distinct spatial patterns of virus communities Fig.  may be c6. This study shows that some of these attributes are already being attained, but additional innovation and interest will be required to get up to speed on all fronts. Post-pandemic society will require orthogonal, comprehensive viral surveillance of distinct pathogen reservoirs, including wastewater, to better equip epidemiologists with accurate information for public health action.The future of wastewater pathogen monitoring is promising, but responsible parties will need to refine methods to provide timely, comprehensive, and useful informationOur research study complies with institutional review boards from University of Texas MD Anderson Cancer Center and Baylor College of Medicine.Between 100–500 mL of raw wastewater was collected into 500 ml leak-proof prelabeled sample bottles at 6 wastewater treatment plants in Houston, TX and 4 in El Paso, TX. Treatment plants were coded upon the request of public health officials. The surface of the sample bottles was decontaminated with 10% bleach and moved to a “clean” zone, where the samples were sealed into biohazard bags in shipping boxes with absorbent pads and ice packs for overnight shipping to the Alkek Center for Metagenomics and Microbiome Research at Baylor College of Medicine, Houston, TX.Wastewater samples were barcoded upon arrival and stored at 4 °C until processing. First, 50 mL of wastewater was decanted and centrifuged at 3374 x g for 10 min, separating the solid and liquid fractions. The supernatant was then vacuum filtered using an ion-based cellulose filter paper and the virus-containing cellulose filter was placed into a bead-beating tube with lysis buffer. The tube was run on the homogenizer for 1 min at 5 m/s, rested for 1 min, then run on the homogenizer for 1 more minute. Following the bead beating the samples were centrifuged at 14–17×1000 RPM for 2 min. DNA and RNA were extracted using the Qiagen QIAamp VIRAL RNA Mini Kit.RNA extracts were converted to cDNA using Protoscript II First Strand cDNA Synthesis Kit (New England Biolabs Inc.), NEBNext Ultra II Non-Directional RNA Second Strand Module (New England Biolabs Inc.), and Random Primer 6 (New England Biolabs Inc.). A total of 25 ng of the cDNA and DNA mix was used for library construction using Twist Library Preparation EF 2.0 Kit and Twist Universal Adaptor System (Twist Biosciences). The libraries were pooled, a maximum of 16 samples per pool, at equal mass to a total 1,500 ng per pool. The Twist Comprehensive Viral Research Panel (Twist Biosciences) was used to hybridize the probes at 70 °C for 16 h. The post-capture pool was further PCR amplified for 12 cycles and final libraries were sequenced on Illumina NovaSeq 6000 SP flow cell, to generate 2×150 bp paired-end reads. Following sequencing, raw data files in binary base call (BCL) format were converted into FASTQs and demultiplexed based on the dual-index barcodes using the Illumina ‘bcl2fastq’ software.https://www.cdc.gov/coronavirus/2019-ncov/lab/multiplex.html) with a total 20 μl volume containing 5 µl of eluted RNA and 15 µl of TaqPath 1-step Multiplex Master Mix, (A28523 Applied Biosystems) under the following cycling conditions: 25 °C for 2 min, 50 °C for 15 min, 95 °C for 2 min, and 45 cycles of 95 °C for 3 s, then 55 °C for 30 s on a 7500 Fast Dx Real-Time PCR Instrument  with SDS version 1.4 software. The fluorescent signal was measured during the annealing step. Primer sequences and concentration of primers and probes used are available in Supplemental Table 6–710 copies/mL and 16,000-16 copies/mL were run and average CT values of the duplicate wells were used to determine the copy numbers using the standard curve.RT-qPCR for Influenza A and SARS-CoV-2 was carried out using CDC FluSC2 assay  under the following cycling conditions: 45 °C for 10 min, 95 °C for 10 min, and 45 cycles of 95 °C for 15 s, then 55 °C for 1 min. Primer sequences and concentration of primers and probes used are available in Supplemental Table 6 - 850 copies/mL were run and average CT values of the duplicate wells were used to determine the copy numbers using the standard curve.The RSV-A used in the spike-in experiments was isolated from an adult with RSV infection in 2015. Demographics and clinical information were prospectively collected from structured interviews and review of medical records of the subject. The institutional review board of the University of Texas MD Anderson Cancer Center and Baylor College of Medicine approved the study and informed consent was obtained from the participant to test and isolate the sample and consent for future use. Nasal wash sample was inoculated on HEp-2 cells . HEp-2 cells were maintained in Eagle’s Minimum Essential Medium (MEM), (Mediatech) supplemented with 10% fetal bovine serum (FBS) (Hyclone), 2 mM glutamine and antibiotic and anti-mycotic (Gibco Life Technologies). After initial isolation, the working stock was prepared by passing RSV four times to make working pools. Viral working stocks are made by infecting Hep-2 cells at a multiplicity of infection of 0.1 in MEM supplemented with 2% FBS, 2 mM glutamine and antibiotic and anti-mycotic. Infection is monitored for 2–3 days until 75% cytopathic effect is achieved. RSV is harvested by disrupting the cell monolayer with sterile glass beads and the resulting cell suspension was sonicated at 60 W for 2 min (Branson sonicator). The viral suspension was clarified by centrifugation and diluted 1:1 in Iscoves modified Dulbecco’s medium and 15% glycerol. Viral aliquot stocks of 1 ml were snap frozen in ethanol and dry ice bath, and stored at −70 °C. The viral stocks contained 1.53 × 10https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-790442341).Shape files for Texas counties and cities were downloaded from the US Census TIGER program repository (Virus Pathogen Database (v2.0.2), all available complete isolate genomes for each viral genus covered by the TWIST Comprehensive Virus Research Panel were downloaded from NCBI’s GenBank using Datasets (https://www.ncbi.nlm.nih.gov/datasets/) on November 16th, 2022. Ninety-seven virus genomes were determined to be of highest public health concern based on the subjective opinion of the authors. These genomes were protected from de-replication and segments were concatenated when relevant (available at https://zenodo.org/record/7876309). All other virus genomes and segments were de-replicated at 95% average nucleotide identity and 85% alignment fraction using two rounds of the anicalc/aniclust scripts from CheckV31. Exemplar sequences for each cluster were kept in the database (https://zenodo.org/record/7876309). Hierarchical taxonomic data was obtained for each sequence from the kingdom level to the strain level using Taxonkit32.The TWIST Comprehensive Virus Research Panel is reported to contain over 1 M unique probes that enable detection of 3,153 viral human and nonhuman pathogens. To construct the 33. Processed reads were run through the EsViriru pipeline (v0.1.1) with default settings. Specifically, reads were aligned to the entire Virus Pathogen Database (v2.0.2) via minimap235 and alignments were filtered by CoverM (https://github.com/wwood/CoverM) to require at least 90% average identity across 90% of the read length. Virus genomes/segments with reads covering at least either 1000 nucleotides or 50% of the genome/segment length were considered preliminary detections. Even de-replicated virus sequence sets can have regions that are highly similar between two or more sequences. Consensus sequences from this preliminary set of detected virus genomes/segments were extracted using samtools consensus35. After removing strings of ambiguous N’s, the preliminary consensus sequences were compared to each other pairwise using anicalc, and clusters were made with sequences of at least 98% average identity using aniclust. The longest consensus sequence in each cluster was kept as the final sequence. The fastq reads were then aligned to a smaller database of only the references corresponding to final sequences with the same parameters for minimap2/CoverM. Virus genomes/segments from this alignment with reads covering at least either 1000 nucleotides or 50% of the genome length were considered final detections. The metric RPKMF was calculated as (Reads Per Kilobase of reference genome)/(Million reads passing Filtering). The more common RPKM was not used here and is calculated as (Reads Per Kilobase of reference genome)/(Million reads mapped to reference sequences). This metric was used because, at low levels seen in wastewater, the proportion of reads aligning to virus genomes is presumed to correspond to the proportion of viral nucleic acid molecules over background molecules in the physical sample. Finally, per sample abundance and coverage metrics and taxonomic information were gathered in tabular format and merged into a single table for downstream processing.Demultiplexed raw fastq sequences were processed using BBDuk to quality trim (Q25), remove Illumina adapters, and filter PhiX reads. Reads with a minimum average Phred quality score < 23 and length < 50 bp after trimming were discarded. Trimmed FASTQs were mapped to a combined PhiX (standard Illumina spike in) and human reference genome database (GCF_000001405.39) using BBMap to determine and remove human/PhiX readshttps://github.com/vegandevs/vegan). Plots were made with ggplot36, ggpubr (https://github.com/kassambara/ggpubr), tSNE (https://github.com/jkrijthe/Rtsne), and color packages wesanderson (https://github.com/karthik/wesanderson) and nationalparkcolors . Reads aligning to analyzed reference genomes were processed using iVar37 with default settings and filtered to only report non-synonymous mutations with an allele frequency of at least 3% and a minimum allele coverage of five reads. Dendrogram figures were drawn in R with ggtree38, aplot and ggplot.The tables reporting virus abundance in RPKMF and sample metadata were processed in R, using tidyverse packages. Alpha diversity and Bray-Curtis dissimilarity statistics were calculated using Vegan (https://covid-harriscounty.hub.arcgis.com/). The data from El Paso were obtained from El Paso Public Health upon request. Influenza “Weekly Percentage of Visits with Discharge Diagnosed Influenza” values were manually recorded from weekly Houston Health Department Flu Reports . Monkeypox case numbers were scraped from the Texas Department of State Health Services website and transformed into weekly average cases. After transformation to weekly data, Simple moving average plots with an averaging period of 3 weeks were used to visualize temporal trends with R package tidyquant (https://github.com/business-science/tidyquant). Pearson statistics were used to quantify correlations between data.For each virus analyzed, the wastewater virome abundance was summarized as the mean RPKMF of the relevant genome for all wastewater treatment plants in each city for each week. For Influenza Virus, average RPKMF values for H3N2 and H1N1 were added together. For RT-PCR, genome copies (described above) were averaged across all wastewater treatment plants in each city for each week. SARS-CoV-2 clinical PCR-positive case data and test positivity data were averaged across each week. The data for Houston were obtained at (Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary