Evaluation of bone marrow aspirates using the automated hematology analyzer Sysmex XN-3000.

INTRODUCTION: This study evaluated the feasibility of the Sysmex XN-3000 automated hematology analyzer for the assessment of total nucleated cells (TNC) and bone marrow (BM) cell density in routine bone marrow aspiration (BMA) samples. METHODS: A total of 54 BMA samples from 39 hematological patients were evaluated. The number of megakaryocytes was calculated by a specific gating algorithm using the body fluid mode of the WBC differential (WDF) channel. Lipid contents were calculated through a newly developed algorithm utilizing the WDF channel. The ratio of lipid particles over TNCs by the WNR channel was compared with the BM cellularity assessed by the BM biopsy. The myeloid/erythroid (M/E) ratio was calculated by measuring the number of myeloid cells in the WDF channel and the number of nucleated red blood cells (NRBCs) in the WNR channel. RESULTS: XN-3000 counts and microscopic results showed a linear correlation in TNC (R2  = .98, p < .001), megakaryocytes (R2  = .59, p = .002), NRBC (R2  = .84, p < .001), and M/E ratio (R2  = .59, p < .001). There were significant differences in the lipid/TNC ratios of hypercellular, normocellular, and hypocellular BMs measured by XN-3000 (p < .001). Receiver-operating characteristic analysis detected cut-off values of the lipid/TNC ratio of >0.4054 for hypoplasia and <0.157 for hyperplasia. The sensitivity and specificity for hypoplasia were 100% and 88%, and for hyperplasia were 89% and 86%, respectively. CONCLUSION: XN-3000 provides a quantitative assessment of BM cellularity, supporting the qualitative assessment by myelogram and BM biopsy.

Clinical performance testing of the automated haematology analyzer XN-31 prototype using whole blood samples from patients with imported malaria in Japan.

BACKGROUND: The automated haematology analyzer XN-31 prototype (XN-31p) is a new flow cytometry-based device developed to measure the number and the ratio of malaria-infected red blood cells (MI-RBC) with a complete blood count (CBC). The XN-31p can provide results in about one minute and also can simultaneously provide information on the malaria parasite (Plasmodium) species. In this study, clinical testing of the XN-31p was performed using blood samples from patients with imported malaria in Japan. METHODS: Blood samples were collected from 80 patients who visited the hospital of the National Center for Global Health and Medicine, Tokyo, Japan, for malaria diagnosis from January 2017 to January 2019. The test results by the XN-31p were compared with those by other standard methods, such as microscopic observation, rapid diagnostic tests and the nested PCR. RESULTS: Thirty-three patients were diagnosed by the nested PCR as being malaria positive (28 Plasmodium falciparum, 2 Plasmodium vivax, 1 Plasmodium knowlesi, 1 mixed infection of P. falciparum and Plasmodium malariae, and 1 mixed infection of P. falciparum and Plasmodium ovale), and the other 47 were negative. The XN-31p detected 32 patients as "MI-RBC positive", which almost matched the results by the nested PCR and, in fact, completely matched with the microscopic observations. The ratio of RBCs infected with malaria parasites as determined by the XN-31p showed a high correlation coefficient of more than 0.99 with the parasitaemia counted under microscopic observation. The XN-31p can analyse the size and nucleic acid contents of each cell, and the results were visualized on a two-dimensional cytogram termed the "M scattergram". Information on species and developmental stages of the parasites could also be predicted from the patterns visualized in the M scattergrams. The XN-31p showed a positive coincidence rate of 0.848 with the nested PCR in discriminating P. falciparum from the other species. CONCLUSIONS: The XN-31p could rapidly provide instructive information on the ratio of MI-RBC and the infecting Plasmodium species. It was regarded to be of great help for the clinical diagnosis of malaria.

Peripheral granular lymphocytopenia and dysmorphic leukocytosis as simple prognostic markers in COVID-19.

INTRODUCTION: Developing prognostic markers can be useful for clinical decision-making. Peripheral blood (PB) examination is simple and basic that can be performed in any facility. We aimed to investigate whether PB examination can predict prognosis in coronavirus disease (COVID-19). METHODS: Complete blood count (CBC) and PB cell morphology were examined in 38 healthy controls (HCs) and 40 patients with COVID-19. Patients with COVID-19, including 26 mild and 14 severe cases, were hospitalized in Juntendo University Hospital (Tokyo, Japan) between April 1 and August 6, 2020. PB examinations were performed using Sysmex XN-3000 automated hematology analyzer and Sysmex DI-60 employing the convolutional neural network-based automatic image-recognition system. RESULTS: Compared with mild cases, severe cases showed a significantly higher incidence of anemia, lymphopenia, and leukocytosis (P < .001). Granular lymphocyte counts were normal or higher in mild cases and persistently decreased in fatal cases. Temporary increase in granular lymphocytes was associated with survival of patients with severe infection. Red cell distribution width was significantly higher in severe cases than in mild cases (P < .001). Neutrophil dysplasia was consistently observed in COVID-19 cases, but not in HCs. Levels of giant neutrophils and toxic granulation/Döhle bodies were increased in severe cases. CONCLUSION: Basic PB examination can be useful to predict the prognosis of COVID-19, by detecting SARS-CoV-2 infection-induced multi-lineage changes in blood cell counts and morphological anomalies. These changes were dynamically correlated with disease severity and may be associated with disruption of hematopoiesis and the immunological system due to bone marrow stress in severe infection.

Performance of the hematology analyzer XN-31 prototype in the detection of Plasmodium infections in an endemic region of Colombia.

Early and accurate diagnosis is critical in reducing the morbidity and mortality associated with malaria. Microscopy (MI) is the current diagnostic gold standard in the field; however, it requires expert personnel, is time-consuming, and has limited sensitivity. Although rapid diagnostic tests for antigen detection (RDTs) are an alternative to diagnosis, they also have limited sensitivity and produce false positive results in detecting recent past infection. The automated hematology analyzer XN-31 prototype (XN-31p) (Sysmex Corporation, Kobe, Japan) is able to identify plasmodium-infected erythrocytes, count parasitemia and perform complete blood-cell counts within one minute. The performance of the XN-31p in diagnosing malaria was evaluated and compared with real-time polymerase chain reaction (qPCR), MI and RDT in an endemic area of Colombia where Plasmodium falciparum and Plasmodium vivax are present. Acute febrile patients were enrolled from July 2018 to April 2019 in Quibdó, Colombia. Malaria diagnoses were obtained from MI and RDT in the field and later confirmed by qPCR. Venous blood samples in EDTA were processed with an XN-31p in the field. Sensitivity, specificity, positive/negative predictive values, and the likelihood ratios of positive and negative tests were calculated with respect to the results from qPCR, MI and RDT. The intraclass correlation coefficient (ICC) and Bland-Altman plot were used to evaluate the concordance in the parasitemia with respect to MI. A total of 1,754 subjects were enrolled. The mean age was 27.0 years (IQR 14-44); 89.6% were Afro-Colombians, 94.3% lived in urban areas and 0.91% were pregnant. With respect to qPCR, the XN-31p showed a sensitivity of 90% (95% CI 87.24-92.34) and a specificity of 99.83% (95% CI 99.38-99.98) in detecting Plasmodium spp.; both parameters were equivalent to those for MI and RDT. Using MI as the reference, the XN-31p showed a sensitivity of 98.09% (95% CI 96.51-99.08), a specificity of 99.83% (95% CI 99.4-99.98), an ICC of 0.85 (95% CI 0.83-0.87) and an average difference of - 3096 parasites/µL when compared with thick-smear MI and an ICC of 0.98 (95% CI 0.97-0.98) and an average difference of - 0.0013% when compared with thin-smear MI. The XN-31p offers a rapid and accurate alternative method for diagnosing malaria in clinical laboratories in areas where P. falciparum and P. vivax cocirculate.

Automated diagnostic support system with deep learning algorithms for distinction of Philadelphia chromosome-negative myeloproliferative neoplasms using peripheral blood specimen.

Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs) such as polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis are characterized by abnormal proliferation of mature bone marrow cell lineages. Since various non-hematologic disorders can also cause leukocytosis, thrombocytosis and polycythemia, the detection of abnormal peripheral blood cells is essential for the diagnostic screening of Ph-negative MPNs. We sought to develop an automated diagnostic support system of Ph-negative MPNs. Our strategy was to combine the complete blood cell count and research parameters obtained by an automated hematology analyzer (Sysmex XN-9000) with morphological parameters that were extracted using a convolutional neural network deep learning system equipped with an Extreme Gradient Boosting (XGBoost)-based decision-making algorithm. The developed system showed promising performance in the differentiation of PV, ET, and MF with high accuracy when compared with those of the human diagnoses, namely: > 90% sensitivity and > 90% specificity. The calculated area under the curve of the ROC curves were 0.990, 0.967, and 0.974 for PV, ET, MF, respectively. This study is a step toward establishing a universal automated diagnostic system for all types of hematology disorders.

Lysercell M enhances the detection of stage-specific Plasmodium-infected red blood cells in the automated hematology analyzer XN-31 prototype.

The automated hematology analyzers XN-30 (for research) and XN-31 prototype (for diagnosis support) can easily and rapidly detect Plasmodium-infected red blood cells (iRBCs) and distinguish the developmental stages of the parasite in approximately 1 min. Two dedicated reagents, Lysercell M and Fluorocell M, are available with the analyzers. Lysercell M plays an indispensable role in enhancing the fluorescence intensity of the nucleic acid staining dye in Fluorocell M and altering cell morphology. These effects of Lysercell M have been empirically determined but insufficiently analyzed. In this study, the properties of Lysercell M were analyzed using two flow cytometers and a fluorescence microscope. First, the fluorescence intensity emitted by iRBCs treated with Lysercell M or phosphate-buffered saline (PBS) was evaluated. Second, the size of RBCs treated with Lysercell M or PBS was measured. Finally, the morphology of individual parasites was observed after reconstruction of an M scattergram, a cytogram of the XN-31 prototype system, using an imaging flow cytometer. These analyses showed that treatment of iRBCs with Lysercell M increased the fluorescence intensity of stained parasite nucleic acids by approximately 10-fold and reduced the size of iRBCs in a stage-specific manner, facilitating the identification and quantification of ring form, trophozoite, and schizont stage iRBCs. These properties suggest that Lysercell M is useful for rapidly detecting iRBCs and accurately distinguishing the parasite developmental stages, thereby contributing to the usability of the XN-30 and XN-31 prototype analyzers.

Implementation of a red blood cell-optical (RBO) channel for detection of latent iron deficiency anaemia by automated measurement of autofluorescence-emitting red blood cells.

Iron deficiency is the most common and widespread nutritional disorder worldwide. The automated haematology analyser XN-30 (Sysmex, Kobe, Japan) was developed to detect malaria-infected red blood cells (RBCs) in human blood samples using flow cytometry. The optical system of the analyser detects autofluorescence (AF)-emitting RBCs containing iron-deficient haem groups and would aid in the diagnosis of anaemia resulting from iron deficiency. Here, an RBC-optical (RBO) channel was devised and implemented on the analyser. In vitro analyses showed that the analyser detected AF-emitting RBCs treated with 5-aminolevulinic acid. Furthermore, the analyser detected AF-emitting RBCs in mice fed a low iron diet and infected with a rodent malaria parasite; it could also be effectively used in humans. This study demonstrates that the analyser can quantitatively and reproducibly detect AF-emitting RBCs and measure other haematological parameters, suggesting its usefulness for the initial evaluation of latent iron deficiency anaemia in conjunction with the diagnosis of malaria.

A novel automated image analysis system using deep convolutional neural networks can assist to differentiate MDS and AA.

Detection of dysmorphic cells in peripheral blood (PB) smears is essential in diagnostic screening of hematological diseases. Myelodysplastic syndromes (MDS) are hematopoietic neoplasms characterized by dysplastic and ineffective hematopoiesis, which diagnosis is mainly based on morphological findings of PB and bone marrow. We developed an automated diagnostic support system of MDS by combining an automated blood cell image-recognition system using a deep learning system (DLS) powered by convolutional neural networks (CNNs) with a decision-making system using extreme gradient boosting (XGBoost). The DLS of blood cell image-recognition has been trained using datasets consisting of 695,030 blood cell images taken from 3,261 PB smears including hematopoietic malignancies. The DLS simultaneously classified 17 blood cell types and 97 morphological features of such cells with >93.5% sensitivity and >96.0% specificity. The automated MDS diagnostic system successfully differentiated MDS from aplastic anemia (AA) with high accuracy; 96.2% of sensitivity and 100% of specificity (AUC 0.990). This is the first CNN-based automated initial diagnostic system for MDS using PB smears, which is applicable to develop new automated diagnostic systems for various hematological disorders.

Application of the automated haematology analyzer XN-30 for discovery and development of anti-malarial drugs.

BACKGROUND: The erythrocytic stage of Plasmodium falciparum parasites in humans is clinically important, as the parasites at this growth stage causes malarial symptoms. Most of the currently available anti-malarial drugs target this stage, but the emergence and spread of parasites resistant to anti-malarial drugs are a major challenge to global eradication efforts; therefore, the development of novel medicines is urgently required. In this study, the in vitro anti-malarial activity of five current anti-malarial drugs (artemisinin, atovaquone, chloroquine, mefloquine, and pyrimethamine) and 400 compounds from the Pathogen Box provided by the Medicines for Malaria Venture on P. falciparum parasites was characterized using the XN-30 analyzer. Furthermore, the outcomes obtained using the analyser were classified according to the parasitaemias of total and each developmental stages. RESULTS: The growth inhibition rate and the half-maximal (50%) inhibitory concentration (IC50) of the five current anti-malarial drugs were calculated from the parasitaemia detected using the XN-30 analyzer. Respective strains and drugs presented strongly fitted sigmoidal curves, and the median SD at all tested concentrations was 1.6, suggesting that the variation in values measured with the analyser was acceptably low for the comparison of drug efficacy. Furthermore, the anti-malarial activity of the 400 compounds from the Pathogen Box was tested, and 141 drugs were found to be effective. In addition, the efficacy was classified into 4 types (Type I, parasites were arrested or killed without DNA replication; Type II, parasites were arrested or killed similar to Type I, and the parasitaemia was apparently decreased; Type III, parasites progressed to trophozoite without sufficient DNA replication; and Type IV, parasites were arrested at late trophozoite or schizont after DNA replication). CONCLUSION: The current study demonstrates that the XN-30 analyzer objectively, reproducibly, and easily evaluated and characterized the anti-malarial efficacy of various compounds. The results indicate the potential of the XN-30 analyzer as a powerful tool for drug discovery and development in addition to its use as an important diagnostic tool.

Application of the automated haematology analyzer XN-30 in an experimental rodent model of malaria.

BACKGROUND: The erythrocytic stage, where malaria parasites proliferate in human blood, is clinically significant as this causes the symptoms and illness of malaria. Experimental rodent models of malaria at the erythrocytic stage are used for the development of anti-malarial drugs and for biological analysis. An automated haematology analyzer XN-30 was developed for detection of infected red blood cells (iRBCs) in human blood samples and measurement of their parasitaemia in approximately 1 min through flow cytometry analysis. Additionally, the analyzer simultaneously measured other haematological parameters in these samples. It is inferred that the analyzer would also allow easy and rapid measurement of parasitaemia in mice and provide important clues on the mouse haematological state during infection and treatment. RESULTS: The XN-30 analyzer is a simple and rapid tool to detect iRBCs in mouse blood samples infected with rodent malarial parasites, with three-dimensional analysis permitting the precise measurement of parasitaemia (referred herein as the 'XN-30 system'). The XN-30 analyzer allowed not only the detection of iRBCs but also the monitoring of RBC, white blood cell, and platelet counts, as well as haematocrit, mean corpuscular volume and mean platelet volume values in the mouse blood sample. For anti-malarial drug development, aside from demonstrating possible efficacy in mouse models, XN-30 analyzer could provide a first glimpse of the safety profile of the drug. CONCLUSIONS: The XN-30 system is a powerful tool that can be utilized for the in vivo screening, development, and evaluation of anti-malarial drugs as well as for pre-clinical pharmacology and/or toxicity tests in rodent models.

Evaluation of cell count and classification capabilities in body fluids using a fully automated Sysmex XN equipped with high-sensitive Analysis (hsA) mode and DI-60 hematology analyzer system.

The XN series automated hematology analyzer has been equipped with a body fluid (BF) mode to count and differentiate leukocytes in BF samples including cerebrospinal fluid (CSF). However, its diagnostic accuracy is not reliable for CSF samples with low cell concentration at the border between normal and pathologic level. To overcome this limitation, a new flow cytometry-based technology, termed "high sensitive analysis (hsA) mode," has been developed. In addition, the XN series analyzer has been equipped with the automated digital cell imaging analyzer DI-60 to classify cell morphology including normal leukocytes differential and abnormal malignant cells detection. Using various BF samples, we evaluated the performance of the XN-hsA mode and DI-60 compared to manual microscopic examination. The reproducibility of the XN-hsA mode showed good results in samples with low cell densities (coefficient of variation; % CV: 7.8% for 6 cells/µL). The linearity of the XN-hsA mode was established up to 938 cells/µL. The cell number obtained using the XN-hsA mode correlated highly with the corresponding microscopic examination. Good correlation was also observed between the DI-60 analyses and manual microscopic classification for all leukocyte types, except monocytes. In conclusion, the combined use of cell counting with the XN-hsA mode and automated morphological analyses using the DI-60 mode is potentially useful for the automated analysis of BF cells.

Novel flowcytometry-based approach of malignant cell detection in body fluids using an automated hematology analyzer.

Morphological microscopic examinations of nucleated cells in body fluid (BF) samples are performed to screen malignancy. However, the morphological differentiation is time-consuming and labor-intensive. This study aimed to develop a new flowcytometry-based gating analysis mode "XN-BF gating algorithm" to detect malignant cells using an automated hematology analyzer, Sysmex XN-1000. XN-BF mode was equipped with WDF white blood cell (WBC) differential channel. We added two algorithms to the WDF channel: Rule 1 detects larger and clumped cell signals compared to the leukocytes, targeting the clustered malignant cells; Rule 2 detects middle sized mononuclear cells containing less granules than neutrophils with similar fluorescence signal to monocytes, targeting hematological malignant cells and solid tumor cells. BF samples that meet, at least, one rule were detected as malignant. To evaluate this novel gating algorithm, 92 various BF samples were collected. Manual microscopic differentiation with the May-Grunwald Giemsa stain and WBC count with hemocytometer were also performed. The performance of these three methods were evaluated by comparing with the cytological diagnosis. The XN-BF gating algorithm achieved sensitivity of 63.0% and specificity of 87.8% with 68.0% for positive predictive value and 85.1% for negative predictive value in detecting malignant-cell positive samples. Manual microscopic WBC differentiation and WBC count demonstrated 70.4% and 66.7% of sensitivities, and 96.9% and 92.3% of specificities, respectively. The XN-BF gating algorithm can be a feasible tool in hematology laboratories for prompt screening of malignant cells in various BF samples.

An automated haematology analyzer XN-30 distinguishes developmental stages of falciparum malaria parasite cultured in vitro.

BACKGROUND: The automated haematology analyzer XN-30 (Sysmex, Kobe, Japan) easily and rapidly detects malarial parasites in clinical blood samples using flow cytometry. The XN-30 analyzer is able to distinguish each developmental stage by measuring DNA content and cell size. Thus, it was expected to be capable of quantifying the developmental stages of cultured falciparum parasite. To achieve this requirement, a modified algorithm was tested for its validity and reliability using in vitro cultured falciparum parasite. RESULTS: The XN-30 analyzer automatically measured each developmental stage as well as total parasitaemia. Comparison of the parasitaemia obtained using the XN-30 analyzer equipped with the modified algorithm with that obtained using microscopy examination of Giemsa-stained smears revealed the greater sensitivity and reproducibility of the former. The XN-30 analyzer also detected free merozoites and purified gametocytes. CONCLUSIONS: The XN-30 analyzer allows the precise recognition and enumeration of total and each developmental stages of cultured falciparum parasites, and permits the sensitive and reproducible calculation of parasitaemia. The results indicate the potential of the XN-30 analyzer for basic research on malarial biology, anti-malarial drug discovery, and evaluation of drug efficacy.

"Aged sample" software on automated routine hematology analyzer enables differentiation between pathological and non-pathological WBC flagging in aging samples.

BACKGROUND: Storing K(x)EDTA-conjugated blood samples at room temperature or under insufficient cooling conditions results in various morphological changes such as swelling of the blood cells. These changes are reproducible and have already been described well. However, they can lead to incorrect flagging when using automated hematology analyzers for complete blood counts and white blood cell differentials. The aim of this study was to determine if those changes can be detected automatically and used to prevent false positive flagging. METHODS: 150 blood samples were aged under controlled conditions and the impact on the "Aged sample" software was checked retrospectively. The results were verified in a second retrospective study including 6288 routine samples. RESULTS: When tested in a routine laboratory, the "Aged sample" software was able to reduce overall flagging by 23% without increasing false negative flagging. CONCLUSIONS: The "Aged sample" software of XN-Series analyzers does not only detect and flag samples that are aging or were stored under suboptimal conditions but also prevents false positive flagging.

Foxp3 expression on normal and leukemic CD4+CD25+ T cells implicated in human T-cell leukemia virus type-1 is inconsistent with Treg cells.

Foxp3 is a master gene of Treg cells, a novel subset of CD4(+) T cells primarily expressing CD25. We describe here different features in Foxp3 expression profile between normal and leukemic CD4(+)CD25(+) T cells, using peripheral blood samples from healthy controls (HCs), human T-cell leukemia virus type-1 (HTLV-1)-infected asymptomatic carriers (ACs), patients with adult T-cell leukemia (ATL), and various hematopoietic cell lines. The majority of CD4(+)CD25(+) T cells in HCs were positive for Foxp3, but not all CD4(+)CD25(+) T cells in ACs were positive, indicating that Foxp3 expression is not always linked to CD25 expression in normal T cells. Leukemic (ATL) T cells constitutively expressing CD25 were characteristic of heterogeneous Foxp3 expression, such as intra- and inter-case heterogeneity in intensity, inconsistency with CD25 expression, and a discrepancy in the mRNA and its protein expression. Surprisingly, a discernible amount of Foxp3 mRNA was detectable even in most cell lines without CD25 expression, a small fraction of which was positive for the Foxp3 proteins. The subcellular localization of Foxp3 in HTLV-1-infected cell lines was mainly cytoplasmic, different from that of primary ATL cells. These findings indicate that Foxp3 has two facets: essential Treg identity and molecular mimicry secondary to tumorigenesis. Conclusively, Foxp3 in normal T cells, but not mRNA, is basically potent at discriminating a subset of Treg cells from CD25(+) T-cell populations, whereas the modulation of Foxp3 expression in leukemic T cells could be implicated in oncogenesis and has a potentially useful clinical role.

Improved detection of minimal acute myeloid leukemia cells by the use of the combined parameters of XE-2100 hematology analyzer.

BACKGROUND: For the diagnosis and therapy of acute leukemia, it is important to detect a small number of leukemic cells precisely. Although several automated hematology analyzers that carry blast-detecting programs have been developed, they do not exert sufficient detection sensitivity to exceed the sensitivity of manual eye counting method. METHODS: We constructed a new blast-detecting program by combining the numerical information acquired from five cytometric parameters presented by XE-2100. The sensitivity and specificity of this blast multi-scoring program were assessed in comparison with the Blasts flag program equipped originally in XE-2100. RESULTS: The blast-detecting sensitivity was found to be highly improved in the blast multi-scoring program as compared with the Blasts flag program without much decreasing the specificity. A small number of leukemic myeloblasts was detected at the better sensitivity than the eye counting method in the clinical course of the patients with acute myeloid leukemia. CONCLUSIONS: The daily practical use of this blast multi-scoring program will surely contribute to sensitive, objective, and real-time evaluation of the control of acute myeloid leukemia with a low cost.

Mutational analysis of the metabolism of 2,6-naphthalenedisulfonate by Pigmentiphaga sp. NDS-2.

The metabolism of 2,6-naphthalenedisulfonate (26NDS) by Pigmentiphaga sp. NDS-2 was analyzed by isolating a mutant (NDS2-002) which slowly grew on a minimal medium containing 26NDS as the sole source of carbon. Liquid chromatography/mass spectrometry (LC/MS) analysis of metabolic intermediates in this strain revealed that 5-sulfosalicylate (5SSA) is accumulated during the degradation of 26NDS. To analyze the lower metabolic pathway, a mutant strain NDS2-008, which could not grow either on 26NDS, 5SSA or gentisate, but could on succinate as the carbon source, was isolated. When the resting cells of NDS2-008 were incubated with 5SSA or gentisate, a substance deduced to be maleylpyruvate (Zhou et al., J. Bacteriol., 183, 700-708, 2001) was commonly detected upon HPLC analysis. These results suggest that Pigmentiphaga sp. NDS-2 degrades 26NDS via 5SSA, gentisate and maleylpyruvate as intermediates.