Automatic segmentation of nuclei in 3D microscopy images is essential for many biological studies including high throughput analysis of gene expression level, morphology, and phenotypes in single cell level. The complexity and variability of the microscopy images present many difficulties to the traditional image segmentation methods. In this paper, we present a new method based on 3D watershed algorithm to segment such images. By using both the intensity information of the image and the geometry information of the appropriately detected foreground mask, our method is robust to intensity fluctuation within nuclei and at the same time sensitive to the intensity and geometrical cues between nuclei. Besides, the method can automatically correct potential segmentation errors by using several post-processing steps. We tested this algorithm on the 3D confocal images of C.elegans, an organism that has been widely used in biological studies. Our results show that the algorithm can segment nuclei in high accuracy despite the non-uniform background, tightly clustered nuclei with different sizes and shapes, fluctuated intensities, and hollow-shaped staining patterns in the images.

C. elegans, a roundworm in soil is widely used in studying animal development and aging, cell differentiation, etc. Recentlv, high-resolution fluorescence images of C. elegans have become available, introducing several new image analysis applications. One problem is that worm bodies usually curve greatly in images, thus it is highly desired to straighten worms so that they can be compared easily under the same canonical coordinate system. We develop a worm straightening algorithm (WSA) using a cutting-plane restacking method, which aggregates the linear rotation transforms of a continuous sequence of cutting lines/planes orthogonal to the "backbone" of a worm to best approximate the nonlinearly bended worm body. We formulate the backbone as a parametric form of cubic spline of a series of control points. We develop two minimum-spanning-tree based methods to automatically determine the locations of control points. Our experimental methods show that our approach can effectively straighten both 2D and 3D worm images.

When searching sequence databases for RNAs, it is desirable to score both primary sequence and RNA secondary structure similarity. Covariance models (CMs) are probabilistic models well-suited for RNA similarity search applications. However, the computational complexity of CM dynamic programming alignment algorithms has limited their practical application. Here we describe an acceleration method called query-dependent banding (QDB), which uses the probabilistic query CM to precalculate regions of the dynamic programming lattice that have negligible probability, independently of the target database. We have implemented QDB in the freely available Infernal software package. QDB reduces the average case time complexity of CM alignment from LN(2.4) to LN(1.3) for a query RNA of N residues and a target database of L residues, resulting in a 4-fold speedup for typical RNA queries. Combined with other improvements to Infernal, including informative mixture Dirichlet priors on model parameters, benchmarks also show increased sensitivity and specificity resulting from improved parameterization.

Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.

CA1 pyramidal neurons from animals that have acquired hippocampal tasks show increased neuronal excitability, as evidenced by a reduction in the postburst afterhyperpolarization (AHP). Studies of AHP plasticity require stable long-term recordings, which are affected by the intracellular solutions potassium methylsulphate (KMeth) or potassium gluconate (KGluc). Here we show immediate and gradual effects of these intracellular solutions on measurement of the AHP and basic membrane properties, and on the induction of AHP plasticity in CA1 pyramidal neurons from rat hippocampal slices. The AHP measured immediately after establishing whole-cell recordings was larger with KMeth than with KGluc. In general, the AHP in KMeth was comparable to the AHP measured in the perforated-patch configuration. However, KMeth induced time-dependent changes in the intrinsic membrane properties of CA1 pyramidal neurons. Specifically, input resistance progressively increased by 70% after 50 min; correspondingly, the current required to trigger an action potential and the fast afterdepolarization following action potentials gradually decreased by about 50%. Conversely, these measures were stable in KGluc. We also demonstrate that activity-dependent plasticity of the AHP occurs with physiologically relevant stimuli in KGluc. AHPs triggered with theta-burst firing every 30 s were progressively reduced, whereas AHPs elicited every 150 s were stable. Blockade of the apamin-sensitive AHP current (I(AHP)) was insufficient to block AHP plasticity, suggesting that plasticity is manifested through changes in the apamin-insensitive slow AHP current (sI(AHP)). These changes were observed in the presence of synaptic blockers, and therefore reflect changes in the intrinsic properties of the neurons. However, no AHP plasticity was observed using KMeth. In summary, these data show that KMeth produces time-dependent changes in basic membrane properties and prevents or obscures activity-dependent reduction of the AHP. In whole-cell recordings using KGluc, repetitive theta-burst firing induced AHP plasticity that mimics learning-related reduction in the AHP.

We introduce a method for optically imaging intracellular proteins at nanometer spatial resolution. Numerous sparse subsets of photoactivatable fluorescent protein molecules were activated, localized (to approximately 2 to 25 nanometers), and then bleached. The aggregate position information from all subsets was then assembled into a superresolution image. We used this method–termed photoactivated localization microscopy–to image specific target proteins in thin sections of lysosomes and mitochondria; in fixed whole cells, we imaged vinculin at focal adhesions, actin within a lamellipodium, and the distribution of the retroviral protein Gag at the plasma membrane.

Commentary: The original PALM paper by myself and my friend and co-inventor Harald Hess, spanning the before- and after-HHMI eras. Submitted and publicly presented months before other publications in the same year, the lessons of the paper remain widely misunderstood: 1) localization precision is not resolution; 2) the ability to resolve a few molecules by the Rayleigh criterion in a diffraction limited region (DLR) does not imply the ability to resolve structures of arbitrary complexity at the same scale; 3) true resolution well beyond the Abbe limit requires the ability to isolate and localize hundreds or thousands of molecules in one DLR; and 4) certain photoactivatable fluorescent proteins (PA-FPs) and caged dyes can be isolated and precisely localized at such densities; yielding true resolution down to  20 nm. The molecular densities we demonstrate (105 molecules/m2) are more than two orders of magnitude greater than in later papers that year (implying ten-fold better true resolution) – indeed, these papers demonstrate densities only comparable to earlier spectral or photobleaching based isolation methods. We validate our claims by correlative electron microscopy, and demonstrate the outstanding advantages of PA-FPs for superresolution microscopy: minimally perturbative sample preparation; high labeling densities; close binding to molecular targets; and zero non-specific background.

Janelia Farm, the new research campus of the Howard Hughes Medical Institute, is an ongoing experiment in the social engineering of research communities.

The patch-clamp technique allows investigation of the electrical excitability of neurons and the functional properties and densities of ion channels. Most patch-clamp recordings from neurons have been made from the soma, the largest structure of individual neurons, while their dendrites, which form the majority of the surface area and receive most of the synaptic input, have been relatively neglected. This protocol describes techniques for recording from the dendrites of neurons in brain slices under direct visual control. Although the basic technique is similar to that used for somatic patching, we describe refinements and optimizations of slice quality, microscope optics, setup stability and electrode approach that are required for maximizing the success rate for dendritic recordings. Using this approach, all configurations of the patch-clamp technique (cell-attached, inside-out, whole-cell, outside-out and perforated patch) can be achieved, even for relatively distal dendrites, and simultaneous multiple-electrode dendritic recordings are also possible. The protocol--from the beginning of slice preparation to the end of the first successful recording--can be completed in 3 h.